Showing papers in "Journal of Electronic Imaging in 1998"
TL;DR: A new image compression technique called DjVu is presented that enables fast transmission of document images over low-speed connections, while faithfully reproducing the visual aspect of the document, including color, fonts, pictures, and paper texture.
312 citations
TL;DR: This poster presents a poster presenting a probabilistic procedure for estimating the response of the immune system to laser-spot assisted treatment of central nervous system injuries.
Abstract: Keywords: LTS1 Reference LTS-ARTICLE-1998-011doi:10.1117/1.482648View record in Web of Science Record created on 2006-06-14, modified on 2016-08-08
270 citations
TL;DR: A new product cipher which encrypts large blocks of plaintext by repeated intertwined application of substitution and permutation operations is introduced, which offers many features that make them superior to contemporary bulk encryption systems when aiming at efficient image and video data encryption.
Abstract: To guarantee security and privacy in image and video archival applications, efficient bulk encryption techniques are necessary which are easily implementable in soft- and hardware and are able to cope with the vast amounts of data involved. Experience has shown that block-oriented symmetric product ciphers constitute an adequate design paradigm for resolving this task, since they can offer a very high level of security as well as very high encryption rates. In this contribution we introduce a new product cipher which encrypts large blocks of plaintext by repeated intertwined application of substitution and permutation operations. While almost all of the current product ciphers use fixed (predefined) permutation operations on small data blocks, our approach involves parametrizable (keyed) permutations on large data blocks (whole images) induced by specific chaotic systems (Kolmogorov flows). By combining these highly unstable dynamics with an adaption of a very fast shift register based pseudo-random number generator, we obtain a new class of computationally secure product ciphers which offer many features that make them superior to contemporary bulk encryption systems when aiming at efficient image and video data encryption. © 1998 SPIE and IS&T.
196 citations
TL;DR: A content-based temporal video segmentation system that integrates syntactic and semantic features for auto- matic management of video data and a new unsupervised scene change detection method based on two-class clustering is introduced to eliminate the data dependency of threshold selection.
Abstract: This paper proposes a content-based temporal video segmentation system that integrates syntactic (domain- independent) and semantic (domain-dependent) features for auto- matic management of video data. Temporal video segmentation in- cludes scene change detection and shot classification. The proposed scene change detection method consists of two steps: detection and tracking of semantic objects of interest specified by the user, and an unsupervised method for detection of cuts, and edit effects. Object detection and tracking is achieved using a region matching scheme, where the region of interest is defined by the boundary of the object. A new unsupervised scene change detec- tion method based on two-class clustering is introduced to eliminate the data dependency of threshold selection. The proposed shot classification approach relies on semantic image features and ex- ploits domain-dependent visual properties such as shape, color, and spatial configuration of tracked semantic objects. The system has been applied to segmentation and classification of TV programs col- lected from different channels. Although the paper focuses on news programs, the method can easily be applied to other TV programs with distinct semantic structure. © 1998 SPIE and IS&T. (S1017-9909(98)00803-4)
142 citations
IBM1
TL;DR: A new method for invisibly watermarking high-quality color and gray-scale images intended for use in image verification applications to determine whether the content of an image has been altered, due perhaps, to the act of a malicious party.
Abstract: In this paper we propose a new method for invisibly wa- termarking high-quality color and gray-scale images. This method is intended for use in image verification applications to determine whether the content of an image has been altered, due perhaps, to the act of a malicious party. It consists of both a watermarking pro- cess which stamps a watermark into a source image without visual degradation, and a watermark extraction process which extracts a watermark from a stamped image. The extracted watermark can be compared with the embedded watermark to determine whether the image has been altered. The processing used in the watermarking and watermark extraction processes will be presented in this paper. In addition, we shall describe some modifications that provide better security, and an adaptation of the scheme to watermark JPEG im- ages. Experimental results are reported. Some advantages of this technique over other invisible watermarking techniques for verifica- tion will be discussed; these include a high degree of invisibility, color preservation, ease of extraction, and a high degree of protec- tion against the retention of a correct watermark after alteration by a malicious party. © 1998 SPIE and IS&T. (S1017-9909(98)00903-9)
134 citations
TL;DR: An optimized spatial-domain implementation of the Gabor transform, using one-dimensional 11-tap filter masks, that is faster and more flexible than Fourier implementations, and two ways to incorporate a high-pass residual, which permits a visually complete representation of the image.
Abstract: Gabor schemes of multiscale image representation are useful in many computer vision applications. However, the classic Gabor expansion is computationally expensive due to the lack of orthogonality of Gabor functions. Some alternative schemes, based on the application of a bank of Gabor filters, have important advantages such as computational efficiency and robustness, at the cost of redundancy and lack of completeness. In a previous work we proposed a quasicomplete Gabor transform, suitable for fast implementations in either space or frequency domains. Reconstruction was achieved by simply adding together the even Gabor channels. We develop an optimized spatial-domain implementation, using one-dimensional 11-tap filter masks, that is faster and more flexible than Fourier implementations. The reconstruction method is improved by applying fixed and independent weights to the Gabor channels before adding them together. Finally, we analyze and implement, in the spatial domain, two ways to incorporate a high-pass residual, which permits a visually complete representation of the image. © 1998 SPIE and IS&T.
130 citations
TL;DR: This chapter discusses wavelet Image and Video Compression, which is concerned with subband video Coding, and its application to time-Frequency analysis, Wavelets and Filter Banks.
Abstract: 1 Introduction PN Topiwala I: Preliminaries 2 Preliminaries PN Topiwala 3Time-Frequency Analysis, Wavelets and Filter Banks PN Topiwala 4 Introduction to Compression PN Topiwala 5 Symmetric Extension Transforms CM Brislawn II: Still Image Coding 6 Wavelet Still Image Coding: A Baseline MSE and HVS Approach PN Topiwala 7 Image Coding Using Multiplier-Free Filter Banks A Docef, et al 8 Embedded Image Coding Using Zerotrees of Wavelet Coefficients JM Shapiro 9 A New Fast/Efficient Image Codec Based on Set Partitioning in Hierarchical Trees A Said, WA Pearlman 10 Space-Frequency Quantization for Wavelet Image Coding Zixiang Xiong, et al 11 Suband Coding of Images Using Classification and Trellis Coded Quantization R Joshi, TR Fisher 12 Low-Complexity Compression of Run Length Coded Image Subbands JD Villasenor, Jiangtao Wen III: Special Topics in Still Image Coding 13 Fractal Image Coding as Cross-Scale Wavelet Coefficient Prediction G Davis 14 Region of Interest Compression in Subband Coding PN Topiwala 15 Wavelet-Based Embedded Multispectral Image Compression PN Topiwala 16 The FBI Fingerprint Image Compression Specification CM Brislawn 17 Embedded Image Coding Using Wavelet Difference Reduction Jun Tian, RO Wells, Jr 18 Block Transforms in Progressive Image Coding Trac D Tran, Truong Q Nguyen IV: Video Coding 19 Brief on Video Coding Standards PN Topiwala 20 Interpolative Multiresolution Coding of Advanced TV with Subchannels KM Uz, et al 21 Subband Video Coding for Low to High Rate Applications WC Chung, et al 22 Very Low Bit Rate Video Coding Based on Matching Pursuits R Neff, A Zakhor 23 Object-Based Subband/Wavelet Video Compression Soo-Chul Han, JW Woods 24 Embedded Video Subband Coding with 3D SPIHT WA Pearlman, et al A: Wavelet Image and Video Compression -- The Homepage PN Topiwala B: The Authors C: Index
100 citations
93 citations
TL;DR: This so-called watermarking process is intended to be the basis of a complete copyright protection system and consists of constructing a band-limited image from binary sequences with good correlation properties and in modulating some randomly selected carriers.
Abstract: In this paper, we wish to present a process enabling us to mark digital pictures with invisible and undetectable secret information. This so-called watermarking process is intended to be the basis of a complete copyright protection system. It consists of constructing a band-limited image from binary sequences with good correlation properties and in modulating some randomly selected carriers. The security relies on the secrecy of these carrier frequencies, which are deduced from a unique secret key. Then the amplitude of the modulated images is modified according to a masking criterion based on a model of the Human Visual System. The adding of the modulated images to the original is supposed to be invisible. The resulting image fully identifies the copyright owner since he is the only one able to detect and prove the presence of the embedded watermark thanks to his secret key. This paper also contains an analysis of the robustness of the watermark against compression and image processing. (C) 1998 SPIE and IS&T. [S1017-9909(98)01603-1].
90 citations
TL;DR: Ramponi et al. as discussed by the authors proposed an unsharp masking algorithm based on the Laplacian transform, called OS-UM, which is a generalization of the Teager's algorithm.
Abstract: ARationalUnsharpMaskingTechniqueGiovanniRamponiandAndreaPoleselDEEI, University of Triestevia A. Valerio 10,I-34127Trieste,Italye-mail:ramp oni@univ.trieste.itFinal version Nov.1997, accepted for publication in theJournal of Electronic ImagingAbstractThelinearUnsharpMaskingtechniqueusedinimagecontrast enhancementis mo di ed in this pap er,by intro-ducing acontrol term expressedasarational function ofthelo calinputdata.Inthisway,noiseampli cation isavoided and, at the same time, oersho ot e ectson sharpedges are limited. Exp erimental results supp ort the valid-ity of the metho d, even as a prepro cessor for interp olationsystems.Keywords:Image enhancement, Unsharp Masking, Ra-tional lters, Nonlinear op erators.I.IntroductionThe technique of Unsharp Masking (UM) was intro ducedin photography to improve the quality of pictures by mak-ing their details crisp er; it consisted in optically subtractinga blurred copy of an image from the image itself.Its digi-tal version, due to its simplicity and relative e ectiveness,has b ecome a to ol of widespread use in the image pro cess-ing community, describ ed in any textb o ok [1] and includedin many available softwarepackages (e.g.,[2]).Indigitalimage manipulation, it can b erealized as shown in Fig.1,by pro cessing the image with an highpass lter (usually aLaplacian), multiplying the result by a scaling factor, andadding it to the original data.Notwithstanding its p opularity, this technique su ers fromtwo drawbacks which can signi cantly reduceits b ene ts:noise sensitivity and excessiveoversho ot on sharp details.TheformerproblemcomesfromthefactthatUMmetho dassignsanemphasistothehighfrequencycom-p onents of the input, amplifying a part of the sp ectrum inwhich the SNR is usually low.On the opp osite, wide andabrupt luminance transitions in the input image can pro-duce oversho ot e ects; these are put into further evidenceby the human visual system through the Mach band e ect[1].Various mo di cations have b een intro duced in the basicUM technique, in particular to reduce the noise ampli ca-tion problem.A quite trivial approach consists in substi-tuting a bandpass lter for the highpass one in Fig.1. Thisof course reduces noise e ects, but also precludes e ectivedetail enhancement in most images. In more sophisticatedapproaches,nonlinearop erators(orderstatistics,p olyno-mial, logarithmic) are used to generate the correction signalwhichisaddedtotheimage; wewill citeafewof them,without attempting a thorough overview of the eld.Amo di edLaplacian lter,calledtheorderstatistics(OS)Laplacian,isprop osedin[3];itsoutputprop or-tional to the di erence b etween the average and the medianof the pixels in a window. The resulting OS-UM algorithmis evaluated for its p erformance on a convex/concae edgemo del and on white Gaussian noise input signal, showingits robustness and its enhancing characteristics.Alternatively, a p olynomial approach can b e used.In [4],the Laplacian lter is replaced by a simple op erator basedon a generalization of the so-called Teager's algorithm. Un-der reasonable hyp otheses, this op erator approximates theb ehaviour of a lo cal-mean-weighted highpass lter, havingreduced high-frequency gain in dark image areas.Accord-ingtoWeb er'slaw[1],thesensitivityofhumanvi-sualsystemishigherindarkareas;hencetheprop osed lter intro duces a p erceptually smaller noise ampli cation,without diminishing theedge{enhancing capability of theUM metho d.Another p olynomial metho d, the Cubic UM(CUM)technique,hasb eendevised[5]:its purp oseis toamplify onlylo calluminancechangesduetotrueimagedetails.ThisisachievedbymultiplyingtheoutputoftheLaplacian lterbyacontrolsignalobtainedfromquadratic edge sensor.Still in the p olynomial framework,a class of quadratic lters is de ned in [6], where the lterco ecients at a given p osition in the image are calculatedbytakingintoaccountthegreyleveldistributionofsurrounding pixels.A Gaussian or an exp onential functionis used to reduce the contribution of pixel values the lumi-nance of which is di erent from that of the center pixel.Finally, to acquirea b ettercontrol on therangeof theimage brightness,theUMmetho d canb ecoupledto ho-momorphic ltering [1]:in this case, the image is rst con-vertedto thelogarithmic domain, thenUMis p erformedand the output is exp onentiated and scaled [7].To try and cop e with b oth the drawbacks indicated ab ove,i.e.noiseampli cation and excessiveoversho ots,alinearadaptive op erator is prop osed in [8]. The LMS technique isused to change the value of the scaling factor (in Fig.1)at each lo cation of the image; to this purp ose, the pixel tob e pro cessedis lab elled as b elonging to a smo oth area orto a medium{ or high{contrast area.Go o d quality resultscan b eachieved,at theexp enseof a relatively high com-putational complexity. In this pap er we attempt to obtaina similar result with a simpler, non{adaptive metho d.ThebasicUMschemeisstillusedhere,butarationalfunc-1
75 citations
TL;DR: In this article, the authors review the interplay between human vision and electronic imaging, describing how the methods, models and experiments in human vision have influenced the development of imaging systems, and how imaging technologies and ap-plications have raised new research questions for the vision community.
Abstract: . The field of electronic imaging has made incrediblestrides over the past decade producing systems with higher signalquality, complex data formats, sophisticated operations for analyz-ing and visualizing information, advanced interfaces, and richer im-age environments. Since electronic imaging systems and applica-tions are designed for human users, the success of these systemsdepends on the degree to which they match the features of humanvision and cognition. This paper reviews the interplay between hu-man vision and electronic imaging, describing how the methods,models and experiments in human vision have influenced the devel-opment of imaging systems, and how imaging technologies and ap-plications have raised new research questions for the vision com-munity. Using the past decade of papers from the IS&T/SPIEConference on Human Vision and Electronic Imaging as a lens, wetrace a path up the ‘‘perceptual food chain,’’ showing how researchin low-level vision has influenced image quality metrics, image com-pression algorithms, rendering techniques and display design, howresearch in attention and pattern recognition have influenced thedevelopment of image analysis, visualization, and digital librariessystems, and how research in higher-level functions is involved inthe design of emotional, aesthetic, and virtual systems.
TL;DR: A partial embedding two-layer scheme is proposed in which an embedded multiresolution coder generates a lossy base layer, and a simple but effective context-based lossless coder codes the difference between the original image and the lossy reconstruction.
Abstract: Predictive and multiresolution techniques for near-lossless image compression based on the criterion of maximum allowable deviation of pixel values are investigated. A procedure for near-lossless compression using a modification of lossless predictive coding techniques to satisfy the specified tolerance is described. Simulation results with modified versions of two of the best lossless predictive coding techniques known, CALIC and JPEG-LS, are provided. Application of lossless coding based on reversible transforms in conjunction with prequantization is shown to be inferior to predictive techniques for near-lossless compression. A partial embedding two-layer scheme is proposed in which an embedded
multiresolution coder generates a lossy base layer, and a simple but effective context-based lossless coder codes the difference between the original image and the lossy reconstruction. Results show that this lossy plus near-lossless technique yields compression ratios close to those obtained with predictive techniques, while providing the feature of a partially embedded bit-stream.
TL;DR: A new adaptation model, S-LMS, is proposed to compensate for the mixed chromatic adaptation, and results indicated that the human visual system is 60% adapted to the monitor's white point and 40% to ambient light when viewing softcopy images.
Abstract: With the widespread use of color management systems (CMSs), users are now able to achieve device independent color across different media. However, most of the current CMSs guaran- tee the same color only if one sees color under a controlled viewing condition. If one sees color under a different viewing condition, the reproduced color does not match the original. The effect of ambient light on the appearance of the color of softcopy images is discussed in this article. In a typical office environment, a computer graphic monitor with a correlated color temperature (CCT) of 9300 K is widely used under an F6 fluorescent light of 4150 K CCT. In such a case, the human visual system is partially adapted to the CRT moni- tor's white point and partially to the ambient light. A new adaptation model, S-LMS, is proposed to compensate for the mixed chromatic adaptation. Visual experiments were performed to evaluate the mixed chromatic adaptation. Experimental results indicated that hu- man visual system is 60% adapted to the monitor's white point and 40% to ambient light when viewing softcopy images. © 1998 SPIE and IS&T. (S1017-9909(98)00404-8)
TL;DR: The proposed multifeature integration algorithms are designed to offer the user a wide range of options and flex- ibilities in order to enhance the outcome of the search and retrieval operations, and provide a compromise between accuracy and computational complexity.
Abstract: We present algorithms for automatic image annotation and retrieval based on color, shape, texture, and any combination of two or more of these features. Pixel- or region (object)-based color; region-based shape; and block- or region-based texture features have been considered. Automatic region selection has been accom- plished by integrating color and spatial edge features. Color, shape, and texture indexing may be knowledge based (using appropriate training sets) or by example. The multifeature integration algorithms are designed to: (i) offer the user a wide range of options and flex- ibilities in order to enhance the outcome of the search and retrieval operations, and (ii) provide a compromise between accuracy and computational complexity, and vice versa. We demonstrate the per- formance of the proposed algorithms on a variety of images. © 1998 SPIE and IS&T. (S1017-9909(98)02603-8)
TL;DR: In this paper, the authors present efficient key frame selection, feature extraction, indexing, and retrieval techniques that are directly applicable to MPEG compressed video, and demonstrate that these techniques can be used to retrieve similar video scenes from a database, with over 95% recall.
Abstract: To keep pace with the increased popularity of digital video as an archival medium, the development of techniques for fast and efficient analysis of video streams is essential. In particular, solutions to the problems of storing, indexing, browsing, and retrieving video data from large multimedia databases are necessary to allow access to these collections. Given that video is often stored efficiently in a compressed format, the costly overhead of decompression can be reduced by analyzing the compressed representation directly. In earlier work, we presented compressed domain parsing techniques which identified shots, subshots, and scenes. In this article, we present efficient key frame selection, feature extraction, indexing, and retrieval techniques that are directly applicable to MPEG compressed video. We develop a frame type independent representation which normalizes spatial and temporal features including frame type, frame size, macroblock encoding, and motion compensation vectors. Features for indexing are derived directly from this representation and mapped to a low-dimensional space where they can be accessed using standard database techniques. Spatial information is used as primary index into the database and temporal information is used to rank retrieved clips and enhance the robustness of the system. The techniques presented enable efficient indexing, querying, and retrieval of compressed video as demonstrated by our system which typically takes a fraction of a second to retrieve similar video scenes from a database, with over 95% recall.
TL;DR: A new cryptographic method for encrypting still images is proposed, designed on the basis of the base- switching lossless image compression algorithm that simultaneously possesses both image encryption and lossless compression abilities.
Abstract: A new cryptographic method for encrypting still images is proposed. This method is designed on the basis of the base- switching lossless image compression algorithm. The method there- fore simultaneously possesses both image encryption and lossless compression abilities. A given image is first partitioned into nonover- lapping fixed-size subimages, and each subimage will then have its own base value. These subimages are then encoded and encrypted one by one according to the base values. By choosing the function to encrypt the base value, there are (128!) t (or (128!) 3t ) possible ways to encrypt a gray-scaled (color) image if t layers are used in the encryption system. The theoretical analysis needed to support the proposed encryption method is provided, and the experimental results are also presented. © 1998 SPIE and IS&T. (S1017-9909(98)01202-1)
TL;DR: The results of a study on simi- larity evaluation in image retrieval using color, object orientation, and relative position as content features, in a framework oriented to image repositories where the semantics of stored images are limited to a specific domain are described.
Abstract: In this article we describe the results of a study on simi- larity evaluation in image retrieval using color, object orientation, and relative position as content features, in a framework oriented to image repositories where the semantics of stored images are limited to a specific domain. The focus is not on a complete description of image content, which is supposed to be known to some extent, but on the extraction of simple and immediate features that can assure, through their combination, automated image analysis and efficient retrieval. Relevance feedback is introduced as an effective way to improve retrieval accuracy. A simple prototype system is also intro- duced that computes feature descriptors and allows users to enter queries, browse the retrieved images, and refine the results through relevance feedback analysis. © 1998 SPIE and IS&T. (S1017-9909(98)00502-9)
TL;DR: A procedure to determine the optimal block size that minimizes the encoding rate for a typical block-based video coder is derived and this formula shows that the best block size is a function of the accuracy with which the motion vectors are encoded and several parameters related to key characteristics of the video scene.
Abstract: Despite the widespread experience with block-based video coders, there is little analysis or theory that quantitatively explains the effect of block size on encoding bit rate, and ordinarily the block size for a coder is chosen based on empirical experiments on video sequences of interest. In this work, we derive a procedure to determine the optimal block size that minimizes the encoding rate for a typical block-based video coder. To do this, we analytically model the effect of block size and derive expressions for the encoding rates for both motion vectors and difference frames as functions of block size. Minimizing these expressions leads to a simple formula that indicates how to choose the block size in these types of coders. This formula also shows that the best block size is a function of the accuracy with which the motion vectors are encoded and several parameters related to key characteristics of the video scene, such as image texture, motion activity, interframe noise, and coding distortion. We implement the video coder and use our analysis to optimize and explain its performance on real video frames.
TL;DR: The CREW system and format is described, how the correct data can be quickly extracted from a CREW file to support a variety of target devices is shown, and the mechanisms needed for panning, zooming, and fixed-size compression are described.
Abstract: As the applications of digital imagery expand in resolution and pixel fidelity there is a greater need for more efficient compression and extraction of images and subimages. No longer is it
sufficient to compress and decompress an image for a specific target device. The ability to handle many types of image data, extract images at different resolutions and quality, lossless and lossy, zoom and pan, and extract regions-of-interest are the new measures of
image compression system performance. Compression with reversible embedded wavelets (CREW) is a high-quality image compression system that is progressive from high compression to lossless, and pyramidal in resolution. CREW supports regions-of-interest, and multiple image types, such as bi-level and continuous-tone. This paper describes the CREW system and format, shows how the correct data can be quickly extracted from a CREW file to support a variety of target devices, describes the mechanisms needed for panning, zooming, and fixed-size compression, and explains the superior performance on bi-level and graphic images.
TL;DR: Three recent developments in wavelets and subdivision are presented: wavelet-type transforms that map integers to integers, with an application to lossless coding for images, and rate-distortion bounds that realize the compression given by nonlinear approximation theorems for a model where wavelet compression outperforms the Karhunen-Loève approach.
Abstract: We present three recent developments in wavelets and subdivision: wavelet-type transforms that map integers to integers, with an application to lossless coding for images; rate-distortion bounds that realize the compression given by nonlinear approximation theorems for a model where wavelet compression outperforms the Karhunen-Loeve approach; and smoothness results for irregularly spaced subdivision schemes, related to wavelet compression for irregularly spaced data.
TL;DR: A novel technique for segmentation of a JPEG-compressed document based on block activity that can be identi- fied and cropped (or removed from the compressed data without decompressing the image) is presented.
Abstract: We present a novel technique for segmentation of a JPEG-compressed document based on block activity. The activity is measured as the number of bits spent to encode each block. Each number is mapped to a pixel brightness value in an auxiliary image which is then used for segmentation. We introduce the use of such an image and show an example of a simple segmentation algorithm, which was successfully applied to test documents. The document is segmented into characteristics regions labeled as background, half- tones, text, graphics, and continuous tone images. The key feature of the proposed framework is that the desired region can be identi- fied and cropped (or removed) from the compressed data without decompressing the image. © 1998 SPIE and IS&T.
TL;DR: MMach is presented, a fast and comprehensive mathematical morphology toolbox for the KHOROS system dealing with 1-D and 2-D grayscale and binary images and illustrates applications of the toolbox in image analysis.
Abstract: o isrs. ept Abstract. Mathematical morphology is a general theory that studies the decomposition of operators between complete lattices in terms of some families of simple operators: dilations, erosions, antidilations, and antierosions. Nowadays, this theory is largely used in image processing and computer vision to extract information from images. The KHOROS system is an open and general environment for image processing and visualization that has become very popular. One of the main characteristics of KHOROS is its flexibility, since it runs on standard machines, supports several standard data formats, uses a visual programming language, and has tools to help the users to build in and install their own programs. A set of new programs can be organized as a subsystem called a toolbox. We present MMach, a fast and comprehensive mathematical morphology toolbox for the KHOROS system dealing with 1-D and 2-D grayscale and binary images. Each program that is applicable to grayscale and binary images has specialized algorithms for each of these data types, and these algorithms are chosen automatically according to the input data. Several examples illustrate applications of the toolbox in image analysis. © 1998 SPIE and IS&T. [S1017-9909(98)01701-2]
TL;DR: A layered approach to check image compression is proposed in which a check image is represented in several layers, which produces images of better quality than traditional JPEG and wavelet coding methods, especially in the foreground, i.e., the text and graphics.
Abstract: An emerging trend in the banking industry is to digitize checks for storage and transmission. An immediate requirement for efficient storage and transmission is check image compression. General purpose compression algorithms such as JPEG and wavelet-based methods produce annoying ringing or blocking artifacts at high compression ratios. In this paper, a layered approach to check image compression is proposed in which a check image is represented in several layers. The first layer describes the foreground map; the second layer specifies the gray levels of foreground pixels; the third layer is a lossy representation of the background image; and the fourth layer describes the error between the original and the reconstructed image of the first three layers. The layered coding approach produces images of better quality than traditional JPEG and wavelet coding methods, especially in the foreground, i.e., the text and graphics. In addition, this approach allows progressive retrieval or transmission of different image layers.
TL;DR: Two novel histogram-based techniques that are robust to the changes in image illumination levels are proposed that are computationally inexpensive and can also be easily integrated within a wavelet-based image coder.
Abstract: In this article, we propose two novel histogram-based techniques that are robust to the changes in image illumination levels. Given a query image and an image database, current histogram-based techniques retrieve similar images acquired under similar illumination levels. However, these techniques fail when images are acquired under varying illumination conditions. First, we propose employing moments of the image histogram that are invariant to scaling and translation of image gray levels. Second, we propose comparing the parameters of histograms of the wavelet subbands for indexing. These parameters are modified appropriately to counter the effect of changes in illumination. The proposed techniques can be combined to further improve the indexing efficiency. The techniques are computationally inexpensive and can also be easily integrated within a wavelet-based image coder.
TL;DR: From a visual inspection of restored images, it is clear that the proposed adaptive- neighborhood filter provides greater noise suppression than fixed- neighborhood restoration methods.
Abstract: Multiplicative noise is a type of signal-dependent noise where brighter areas of the images appear noisier. A popular class of image restoration methods is based on local mean, median, and variance. However, simple 333 filters do not take the nonstationary nature of the image and/or noise into account, and the restoration achieved by such filters may not be effective. We present a new adaptive-neighborhood or region-based noise filtering technique for restoring images with multiplicative noise. The method is based on finding variable-shaped, variable-sized adaptive neighborhoods for each pixel in the image, followed by the application of a filter spe- cifically designed for multiplicative noise based on statistical param- eters computed over the adaptive neighborhoods. From a visual inspection of restored images, it is clear that the proposed adaptive- neighborhood filter provides greater noise suppression than fixed- neighborhood restoration methods. The proposed method, unlike fixed-neighborhood methods, does not blur or clip object boundaries or corners. The mean squared errors between the results of the proposed method and the original images are considerably lower than those for results of the fixed-neighborhood methods studied, indicating that the image and noise statistics are better estimated by the adaptive-neighborhood method. © 1998 SPIE and IS&T.
TL;DR: It is shown that it is possible to obtain better results in image segmentation when the authors apply the watershed transformation and an algorithm for segmenting images using this class of nonincreasing filters is proposed.
Abstract: In this paper, contrast enhancement and image segmentation are investigated using a class of morphological nonincreasing filters that can be considered toggle mappings. These nonincreasing filters are built using the traditional morphological gradients. These filters have interesting properties and give essential contrast to the images. We apply them sequentially between two or more given
parameters in order to obtain intermediate results. This approach improves the control of the filtering process and provides other tools for contrasting images. We presented several new properties and
one study of the invariant set of these filters. Using these new propositions, we show that it is possible to obtain better results in image segmentation when we apply the watershed transformation.
Also, we propose an algorithm for segmenting images using this class of nonincreasing filters. The method is applied in a geodesic way using two different criteria for segmenting an image. We relate our results with a recent method in mathematical morphology called the flat zone approach and we compare our approach with another method in image processing, the so-called quadtree approach.
TL;DR: It is shown that the optimal set of filters for performing the low-resolution motion compensation is dependent on the choice of down-conversion filter, and the motion compensation filters are determined as the optimal solution of a least squares problem.
Abstract: The most straightforward approach in obtaining a down-converted image sequence is to decimate each frame after it has been fully decoded. To reduce memory requirements and other costs incurred by this approach, a down-conversion decoder would perform a decimation within the decoding loop. In this way, predictions are made from a low-resolution reference which has experienced considerable loss of information. Additionally, the predictions must be made from a set of motion vectors which correspond to the full-resolution image sequence. Given these conditions, it is desirable to optimize the performance of the motion compensation process. In this paper we show that the optimal set of filters for performing the low-resolution motion compensation is dependent on the choice of down-conversion filter. The motion compensation filters are determined as the optimal solution of a least squares problem. This problem is formulated in the context of two general classes of down-conversion techniques: one which is dependent on a single block, and another which is dependent on multiple blocks. General solutions for each class of down-conversion are provided. To demonstrate the usefulness of these results, a sample set of motion compensation filters for each class of down-conversion is calculated, and the results are incorporated into a low-resolution decoder. In comparison to a sub-optimal motion compensation scheme, the optimal motion compensation filters realize a drastic reduction in the amount of drift. Simulation results also reveal that the filters which were based on multiple block down-conversion can reduce the amount of prediction drift found in the single block down-conversion by as much as 35%.
TL;DR: In this article, the authors proposed a method of arbitrarily focused image generation using multiple differently focused images, based on the assumption that depth of a scene changes stepwise, and derive a formula for reconstruction between the desired arbitrarily focused images and multiple acquired images.
Abstract: We propose a novel method of arbitrarily focused image generation using multiple differently focused images. First, we describe our previously proposed select and merge method for all focused image acquisition. We can get good results by using this method but it is not easy to extend this method for generating arbitrarily focused images. Then, based on the assumption that depth of a scene changes stepwise, we derive a formula for reconstruction between the desired arbitrarily focused image and multiple acquired images; we can reconstruct the arbitrarily focused image by iterative use of the formula. We also introduce coarse-to-fine estimation of point spread functions (PSFs) of the acquired images. We reconstruct arbitrarily focused images for a natural scene. In other words, we simulate virtual cameras and generate images focused on arbitrary depths. © 1998 SPIE and IS&T. [S1017-9909(98)02201-6]
TL;DR: A new texture feature, fuzzy texture spectrum, for texture classification, which is based on the relative gray levels be- tween pixels, and it is less sensitive to the noise and the changing of the background brightness in texture images.
Abstract: In the research areas in computer vision, many applica- tions have been discovered using texture classification techniques, such as the content retrieval in multimedia, the computer-aided di- agnosis of medical images, and the segmentation of remote sensing images. The success of the texture classification of a given set of images hinges on the designs of texture features and the classifiers. We present a new texture feature, fuzzy texture spectrum, for tex- ture classification, which is based on the relative gray levels be- tween pixels. A vector of fuzzy values is used to indicate the rela- tionship of the gray levels between the neighboring pixels. The fuzzy texture spectrum can be considered as the distribution of the fuzzi- fied differences between the neighboring pixels. It is an improved version of the reduced texture spectrum, and it is less sensitive to the noise and the changing of the background brightness in texture images. We use 12 Brodatz texture images in the simulations to show the effectiveness of the new texture feature. Our simulation results show that the rate of classification error can be reduced to 0.2083%. © 1998 SPIE and IS&T. (S1017-9909(98)00301-8)
TL;DR: The LTS1 Reference LTS-ARTICLE-1998-005 describes the construction of the Higgs boson particle and some of the properties that contribute to earthquake-triggered landsliding.
Abstract: Keywords: LTS1 Reference LTS-ARTICLE-1998-005View record in Web of Science Record created on 2006-06-14, modified on 2017-05-10