Showing papers on "Image processing published in 1994"

Seeded region growing

Abstract: We present here a new algorithm for segmentation of intensity images which is robust, rapid, and free of tuning parameters. The method, however, requires the input of a number of seeds, either individual pixels or regions, which will control the formation of regions into which the image will be segmented. In this correspondence, we present the algorithm, discuss briefly its properties, and suggest two ways in which it can be employed, namely, by using manual seed selection or by automated procedures. >

Image Processing

Abstract: MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection approach

Abstract: Most applications of hyperspectral imagery require processing techniques which achieve two fundamental goals: 1) detect and classify the constituent materials for each pixel in the scene; 2) reduce the data volume/dimensionality, without loss of critical information, so that it can be processed efficiently and assimilated by a human analyst. The authors describe a technique which simultaneously reduces the data dimensionality, suppresses undesired or interfering spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel vector onto a subspace which is orthogonal to the undesired signatures. This operation is an optimal interference suppression process in the least squares sense. Once the interfering signatures have been nulled, projecting the residual onto the signature of interest maximizes the signal-to-noise ratio and results in a single component image that represents a classification for the signature of interest. The orthogonal subspace projection (OSP) operator can be extended to k-signatures of interest, thus reducing the dimensionality of k and classifying the hyperspectral image simultaneously. The approach is applicable to both spectrally pure as well as mixed pixels. >

A digital watermark

Abstract: The paper discusses the feasibility of coding an "undetectable" digital water mark on a standard 512/spl times/512 intensity image with an 8 bit gray scale. The watermark is capable of carrying such information as authentication or authorisation codes, or a legend essential for image interpretation. This capability is envisaged to find application in image tagging, copyright enforcement, counterfeit protection, and controlled access. Two methods of implementation are discussed. The first is based on bit plane manipulation of the LSB, which offers easy and rapid decoding. The second method utilises linear addition of the water mark to the image data, and is more difficult to decode, offering inherent security. This linearity property also allows some image processing, such as averaging, to take place on the image, without corrupting the water mark beyond recovery. Either method is potentially compatible with JPEG and MPEG processing. >

Representing moving images with layers

Abstract: We describe a system for representing moving images with sets of overlapping layers. Each layer contains an intensity map that defines the additive values of each pixel, along with an alpha map that serves as a mask indicating the transparency. The layers are ordered in depth and they occlude each other in accord with the rules of compositing. Velocity maps define how the layers are to be warped over time. The layered representation is more flexible than standard image transforms and can capture many important properties of natural image sequences. We describe some methods for decomposing image sequences into layers using motion analysis, and we discuss how the representation may be used for image coding and other applications. >

Shape from focus

Abstract: The shape from focus method presented here uses different focus levels to obtain a sequence of object images. The sum-modified-Laplacian (SML) operator is developed to provide local measures of the quality of image focus. The operator is applied to the image sequence to determine a set of focus measures at each image point. A depth estimation algorithm interpolates a small number of focus measure values to obtain accurate depth estimates. A fully automated shape from focus system has been implemented using an optical microscope and tested on a variety of industrial samples. Experimental results are presented that demonstrate the accuracy and robustness of the proposed method. These results suggest shape from focus to be an effective approach for a variety of challenging visual inspection tasks. >

Phase gradient autofocus-a robust tool for high resolution SAR phase correction

Abstract: The phase gradient autofocus (PGA) technique for phase error correction of spotlight mode synthetic aperture radar (SAR) imagery is examined carefully in the context of four fundamental signal processing steps that constitute the algorithm. We demonstrate that excellent results over a wide variety of scene content, and phase error function structure are obtained if and only if all of these steps are included in the processing. Finally, we show that the computational demands of the fun PGA algorithm do not represent a large fraction of the total image formation problem, when mid to large size images are involved. >

What is the goal of sensory coding

Abstract: A number of recent attempts have been made to describe early sensory coding in terms of a general information processing strategy. In this paper, two strategies are contrasted. Both strategies take advantage of the redundancy in the environment to produce more effective representations. The first is described as a "compact" coding scheme. A compact code performs a transform that allows the input to be represented with a reduced number of vectors (cells) with minimal RMS error. This approach has recently become popular in the neural network literature and is related to a process called Principal Components Analysis (PCA). A number of recent papers have suggested that the optimal compact code for representing natural scenes will have units with receptive field profiles much like those found in the retina and primary visual cortex. However, in this paper, it is proposed that compact coding schemes are insufficient to account for the receptive field properties of cells in the mammalian visual pathway. In contrast, it is proposed that the visual system is near to optimal in representing natural scenes only if optimality is defined in terms of "sparse distributed" coding. In a sparse distributed code, all cells in the code have an equal response probability across the class of images but have a low response probability for any single image. In such a code, the dimensionality is not reduced. Rather, the redundancy of the input is transformed into the redundancy of the firing pattern of cells. It is proposed that the signature for a sparse code is found in the fourth moment of the response distribution (i.e., the kurtosis). In measurements with 55 calibrated natural scenes, the kurtosis was found to peak when the bandwidths of the visual code matched those of cells in the mammalian visual cortex. Codes resembling "wavelet transforms" are proposed to be effective because the response histograms of such codes are sparse (i.e., show high kurtosis) when presented with natural scenes. It is proposed that the structure of the image that allows sparse coding is found in the phase spectrum of the image. It is suggested that natural scenes, to a first approximation, can be considered as a sum of self-similar local functions (the inverse of a wavelet). Possible reasons for why sensory systems would evolve toward sparse coding are presented.

Wavelet transform domain filters: a spatially selective noise filtration technique

Abstract: Wavelet transforms are multiresolution decompositions that can be used to analyze signals and images They describe a signal by the power at each scale and position Edges can be located very effectively in the wavelet transform domain A spatially selective noise filtration technique based on the direct spatial correlation of the wavelet transform at several adjacent scales is introduced A high correlation is used to infer that there is a significant feature at the position that should be passed through the filter The authors have tested the technique on simulated signals, phantom images, and real MR images It is found that the technique can reduce noise contents in signals and images by more than 80% while maintaining at least 80% of the value of the gradient at most edges The authors did not observe any Gibbs' ringing or significant resolution loss on the filtered images Artifacts that arose from the filtration are very small and local The noise filtration technique is quite robust There are many possible extensions of the technique The authors see its applications in spatially dependent noise filtration, edge detection and enhancement, image restoration, and motion artifact removal They have compared the performance of the technique to that of the Weiner filter and found it to be superior >

A multiscale random field model for Bayesian image segmentation

Abstract: Many approaches to Bayesian image segmentation have used maximum a posteriori (MAP) estimation in conjunction with Markov random fields (MRF). Although this approach performs well, it has a number of disadvantages. In particular, exact MAP estimates cannot be computed, approximate MAP estimates are computationally expensive to compute, and unsupervised parameter estimation of the MRF is difficult. The authors propose a new approach to Bayesian image segmentation that directly addresses these problems. The new method replaces the MRF model with a novel multiscale random field (MSRF) and replaces the MAP estimator with a sequential MAP (SMAP) estimator derived from a novel estimation criteria. Together, the proposed estimator and model result in a segmentation algorithm that is not iterative and can be computed in time proportional to MN where M is the number of classes and N is the number of pixels. The also develop a computationally efficient method for unsupervised estimation of model parameters. Simulations on synthetic images indicate that the new algorithm performs better and requires much less computation than MAP estimation using simulated annealing. The algorithm is also found to improve classification accuracy when applied to the segmentation of multispectral remotely sensed images with ground truth data. >

Two deterministic half-quadratic regularization algorithms for computed imaging

Abstract: Many image processing problems are ill-posed and must be regularized. Usually, a roughness penalty is imposed on the solution. The difficulty is to avoid the smoothing of edges, which are very important attributes of the image. The authors first give sufficient conditions for the design of such an edge-preserving regularization. Under these conditions, it is possible to introduce an auxiliary variable whose role is twofold. Firstly, it marks the discontinuities and ensures their preservation from smoothing. Secondly, it makes the criterion half-quadratic. The optimization is then easier. The authors propose a deterministic strategy, based on alternate minimizations on the image and the auxiliary variable. This yields two algorithms, ARTUR and LEGEND. The authors apply these algorithms to the problem of SPECT reconstruction. >

A Bayesian approach to image expansion for improved definition

Abstract: Accurate image expansion is important in many areas of image analysis. Common methods of expansion, such as linear and spline techniques, tend to smooth the image data at edge regions. This paper introduces a method for nonlinear image expansion which preserves the discontinuities of the original image, producing an expanded image with improved definition. The maximum a posteriori (MAP) estimation techniques that are proposed for noise-free and noisy images result in the optimization of convex functionals. The expanded images produced from these methods will be shown to be aesthetically and quantitatively superior to images expanded by the standard methods of replication, linear interpolation, and cubic B-spline expansion. >

Multiresolution color image segmentation

Abstract: Image segmentation is the process by which an original image is partitioned into some homogeneous regions. In this paper, a novel multiresolution color image segmentation (MCIS) algorithm which uses Markov random fields (MRF's) is proposed. The proposed approach is a relaxation process that converges to the MAP (maximum a posteriori) estimate of the segmentation. The quadtree structure is used to implement the multiresolution framework, and the simulated annealing technique is employed to control the splitting and merging of nodes so as to minimize an energy function and therefore, maximize the MAP estimate. The multiresolution scheme enables the use of different dissimilarity measures at different resolution levels. Consequently, the proposed algorithm is noise resistant. Since the global clustering information of the image is required in the proposed approach, the scale space filter (SSF) is employed as the first step. The multiresolution approach is used to refine the segmentation. Experimental results of both the synthesized and real images are very encouraging. In order to evaluate experimental results of both synthesized images and real images quantitatively, a new evaluation criterion is proposed and developed. >

Perceptual image distortion

Abstract: In this paper, we present a perceptual distortion measure that predicts image integrity far better than mean-squared error. This perceptual distortion measure is based an a model of human visual processing that fits empirical measurements of the psychophysics of spatial pattern detection. The model of human visual processing proposed involves two major components: a steerable pyramid transform and contrast normalization. We also illustrate the usefulness of the model in predicting perceptual distortion in real images. >

Digital Image Processing: Principles and Applications

Abstract: What Is Image Processing?. Fundamentals of Digital Image Processing. The Digital Image. PROCESSING CONCEPTS. Image Enhancement and Restoration. Image Analysis. Image Compression. Image Synthesis. PROCESSING SYSTEMS. Image Origination and Display. Image Data Handling. Image Data Processing. PROCESSING IN ACTION. Image Operation Studies. Appendices. Glossary. Index.

The Nobeyama radioheliograph

Abstract: A new 17-GHz radio interferometer dedicated for solar observations was constructed in two years at Nobeyama, Nagano It consists of eighty-four 80-cm-diameter antennas arranged in a tee-shaped array extending 490 m in east-west and 220 m in north-south directions Since late June of 1992, radio full-disk images of the Sun have been observed for 8 h every day The spatial resolution is 10" and the temporal resolution is 1 s and also 50 ms for selected events Every 10 s correlator data are synthesized into images in real time and displayed on a monitor screen The array configuration is optimized to observe the whole Sun with high spatial and temporal resolution and a high dynamic range of images Image quality of better than 20 dB is realized by incorporation of technical advances in hardware and software, such as (1) low-loss phase-stable optical-fiber cables for local reference signal and IF signals, (2) newly developed phase-stable local oscillators, (3) custom CMOS gate-array LSTs of 1-b quadraphase correlators for 4/spl times/4 combinations, and (4) new image processing techniques to suppress large sidelobe effects due to the solar disk and extended sources >

Search radar detection and track with the Hough transform. I. system concept

Abstract: A method of viewing search radar signals and data is described and analyzed in which the image processing technique of the Hough transform is used to extract detections and simultaneous tracks from multi-dimensional data maps. System design concepts are considered and simulation examples are given that illustrate the concept. The technique offers many advantages when compared with more traditional techniques. These advantages include improved detection, a solution to the range walk problem, flexibility of implementation, elimination of slow scan-rate latency and automatic track acquisition without revisit. The concept is similar to track-before-detect algorithms that use preliminary information from previous scans to aid in target declarations. >

Two-dimensional imaging

Abstract: 1. Introduction. 2. The Image Plane. 3. Two Dimensional Impulses. 4. The Two Dimensional Fourier Transform. 5. Two Dimensional Convolution. 6. The Convolution Theorem. 7. Sampling and Interpolation in Two Dimensions. 8. Digital Operations. 9. Rotational Symmetry and the Two Dimensional Fourier Transform. 10. Imaging by Convolution. 11. Diffraction Theory of Sensors. 12. Indirect Imaging and Interferometry. 13. Restoration of Images. 14. The Projection-Slice Theorem. 15. Computed Tomography. 16. Synthetic Aperture Radar. 17. Random Images and Fractals. Index.

Fingerprint enhancement by directional Fourier filtering

Abstract: A new method of enhancing fingerprint images is described, based upon nonstationary directional Fourier domain filtering. Fingerprints are first smoothed using a directional filter whose orientation is everywhere matched to the local ridge orientation. Thresholding then yields the enhanced image. Various simplifications lead to efficient implementation on general-purpose digital computers. Results of enhancement are presented for fingerprints of various pattern classifications. A comparison is made with the enhancement used within the automated fingerprint identification system (AFIS) developed by the UK Home Office. Use of the proposed enhancement method leads to significant improvements in the speed and accuracy of the AFIS.

Ridges for Image Analysis

Abstract: Representation of object shape by medial structures has been an important aspect of image analysis. Methods for describing objects in a binary image by medial axes are well understood. Many attempts have been made to construct similar medial structures for objects in gray scale images. In particular, researchers have studied images by analyzing the graphs of the intensity data and identifying ridge and valley structures on those surfaces. In this paper we review many of the definitions for ridges. Computational vision models require that medial structures should remain invariant under certain transformations of the spatial locations and intensities. For each ridge definition we point out which invariances the definition satisfies. We also give extensions of the concepts so that we can located-dimensional ridge structures withinn-dimensional images. A comparison of the ridge structures produced by the different definitions is given both by mathematical examples and by an application to a 2-dimensional MR image of a head.

Airborne SAR processing of highly squinted data using a chirp scaling approach with integrated motion compensation

Abstract: Proposes a new approach for high-resolution airborne SAR data processing, which uses a modified chirp scaling algorithm to accommodate the correction of motion errors, as well as the variations of the Doppler centroid in range and azimuth. By introducing a cubic phase term in the chirp scaling phase, data acquired with a squint angle up to 30/spl deg/ can be processed with no degradation of the impulse response function. The proposed approach is computationally very efficient, since it accommodates the variations of Doppler centroid without using block processing. Furthermore, a motion error extraction algorithm can be incorporated into the proposed approach by means of subaperture processing in azimuth. The new approach, denoted as extended chirp scaling, is considered to be a generalized algorithm suitable for the high-resolution processing of most airborne SAR systems. >

Radiographic image enhancement comparison and storage requirement reduction system

Abstract: A system for processing a radiograph such as an x-ray includes a scanner, a computer with monitor for displaying a digital copy of the radiograph and pet-forming a number of enhancements. The computer stores the digitized image in memory in such a way that it cannot be modified, stores temporarily a second copy of the image in random access memory for display, and stores the enhancements separately in a data file so that, each time the user wishes to see an enhanced image, the enhancements are applied to the displayed digital image as an overlay, rather than being stored as a copy of the enhanced image. Less space is required for storage when only the unenhanced image and the enhancements are stored than if the unenhanced and the enhanced images are stored. Furthermore, not only is the unenhanced image available for a variety of purposes (stored in such a way that it cannot be modified), but the enhancements that are made to produce the enhanced, displayed image are reproduced the same way each time.

Face detection using templates

Abstract: In the problem area of human facial image processing, the first computational task that needs to be solved is that of detecting a face under arbitrary scene conditions. Although some progress towards this has been reported in the literature, face detection remains a difficult problem. In this paper the authors report on a novel face-finding method that appears quite robust. First, "snakelets" are used to find candidate edges. Candidate ovals (face-locations) are then found from these snakelets using a voting method. For each of these candidate face-locations, the authors use a method introduced previously to find detailed facial features. If a substantial number of the facial features are found successfully, and their positions satisfy ratio-tests for being standard, the procedure positively reports the existence of a face at this location in the image.

Real-time image processor

Abstract: A real-time image processor has three functional sections: an image manager, an image processor, and an instruction generator. The image processor may be an array of single-instruction multiple-data (SIMD) processing elements, for processing a subframe of sensor data. The instruction generator generates image processing commands for execution by the image processor. The image manager may be coupled to a plurality of sensors for simultaneously receiving streams of sensor data from the sensors, each stream constituting one or more image frames. When the image manager detects that a subframe of data has been received from a sensor, it loads that subframe into the image processor. Next, the image manager sends a message to the instruction generator, the message including a subframe ready indicator and an algorithm designator. In response, the instruction generator begins generating image processing commands that are determined by the algorithm designator. After the instruction generator has sent out the final image processing command for the designated algorithm, it notifies the image manager. In response, the image manager retrieves the processed image data from the image processor. Hit detection logic in the image manager identifies the location of processed data having predetermined values. The image manager can additionally use a reconstruction buffer to form a processed frame of data from separately processed subframes of data.

Efficient quadtree coding of images and video

Abstract: The quadtree data structure is commonly used in image coding to decompose an image into separate spatial regions to adaptively identify the type of quantizer used in various regions of an image. The authors describe the theory needed to construct quadtree data structures that optimally allocate rate, given a set of quantizers. A Lagrange multiplier method finds these optimal rate allocations with no monotonicity restrictions. They use the theory to derive a new quadtree construction method that uses a stepwise search to find the overall optimal quadtree structure. The search can be driven with either actual measured quantizer performance or ensemble average predicted performance. They apply this theory to the design of a motion compensated interframe video coding system using a quadtree with vector quantization. >

Method and system for searching graphic images and videos

Abstract: A system and method for searching images includes a low level analyzer for processing image data in a plurality of images into side information files, the image data of each side information file pertaining to a particular statistical or perceptual abstraction of the images, such as motion, color, texture, segments, and the like. A user interface allows a user to graphically construct a search inquiry with icons representing image attributes corresponding to the image data in the side information files. A search inquiry may include complex boolean expressions, and custom image attributes may be created to represent useful search inquiries. The image attributes of a search inquiry may also be ranked. A high level analyzer parses a search inquiry to determine the image attributes contained therein, and analyzes the image data of the side information files to determine a similarity measure for each image with respect to the search inquiry. The high level analyzer orders retrieved images according to their similarity measures, and provides them to a image display controller for display. The user may designate selected images that are acceptable matches for the search inquiry. The high level analyzer will then redetermine the rankings and image attribute values, and either reorder previously retrieved images, or perform a new analysis of the image to retrieve a new set of matching images.

Adaptive image region-growing

Abstract: Proposes a simple, yet general and powerful, region-growing framework for image segmentation. The region-growing process is guided by regional feature analysis; no parameter tuning or a priori knowledge about the image is required. To decide if two regions should be merged, instead of comparing the difference of region feature means with a predefined threshold, the authors adaptively assess region homogeneity from region feature distributions. This results in an algorithm that is robust with respect to various image characteristics. The merge criterion also minimizes the number of merge rejections and results in a fast region-growing process that is amenable to parallelization. >