Showing papers on "Quantization (image processing) published in 2002"

Lossless data embedding--new paradigm in digital watermarking

Abstract: One common drawback of virtually all current data embedding methods is the fact that the original image is inevitably distorted due to data embedding itself. This distortion typically cannot be removed completely due to quantization, bit-replacement, or truncation at the grayscales 0 and 255. Although the distortion is often quite small and perceptual models are used to minimize its visibility, the distortion may not be acceptable for medical imagery (for legal reasons) or for military images inspected under nonstandard viewing conditions (after enhancement or extreme zoom). In this paper, we introduce a new paradigm for data embedding in images (lossless data embedding) that has the property that the distortion due to embedding can be completely removed from the watermarked image after the embedded data has been extracted. We present lossless embedding methods for the uncompressed formats (BMP, TIFF) and for the JPEG format. We also show how the concept of lossless data embedding can be used as a powerful tool to achieve a variety of nontrivial tasks, including lossless authentication using fragile watermarks, steganalysis of LSB embedding, and distortion-free robust watermarking.

A steganographic method based upon JPEG and quantization table modification

Abstract: In this paper, a novel steganographic method based on joint photographic expert-group (JPEG) is proposed. The proposed method modifies the quantization table first. Next, the secret message is hidden in the cover-image with its middle-frequency of the quantized DCT coefficients modified. Finally, a JPEG stego-image is generated. JPEG is a standard image and popularly used in Internet. The stego-image will not be suspected if we could apply a JPEG image to data hiding. We compare our method with a JPEG hiding-tool Jpeg-Jsteg. From the experimental results, we obtain that the proposed method has a larger message capacity than Jpeg-Jsteg, and the quality of the stego-images of the proposed method is acceptable. Besides, our method has the same security level as Jpeg-Jsteg.

Compression of digital holograms for three-dimensional object reconstruction and recognition

Abstract: We present the results of applying lossless and lossy data compression to a three-dimensional object reconstruction and recognition technique based on phase-shift digital holography. We find that the best lossless (Lempel-Ziv, Lempel-Ziv-Welch, Huffman, Burrows-Wheeler) compression rates can be expected when the digital hologram is stored in an intermediate coding of separate data streams for real and imaginary components. The lossy techniques are based on subsampling, quantization, and discrete Fourier transformation. For various degrees of speckle reduction, we quantify the number of Fourier coefficients that can be removed from the hologram domain, and the lowest level of quantization achievable, without incurring significant loss in correlation performance or significant error in the reconstructed object domain.

Steganalysis of JPEG Images: Breaking the F5 Algorithm

Abstract: In this paper, we present a steganalytic method that can reliably detect messages (and estimate their size) hidden in JPEG images using the steganographic algorithm F5. The key element of the method is estimation of the cover-image histogram from the stego-image. This is done by decompressing the stego-image, cropping it by four pixels in both directions to remove the quantization in the frequency domain, and recompressing it using the same quality factor as the stego-image. The number of relative changes introduced by F5 is determined using the least square fit by comparing the estimated histograms of selected DCT coefficients with those of the stego-image. Experimental results indicate that relative modifications as small as 10% of the usable DCT coefficients can be reliably detected. The method is tested on a diverse set of test images that include both raw and processed images in the JPEG and BMP formats.

Free-Viewpoint TV system based on Ray-Space representation

Abstract: This paper describes a novel Free-Viewpoint TV system based on Ray-Space representation. This system consists of a multi-view camera system for 3-D data capturing, a PC cluster with 16 PCs for data processing such as data compression and view interpolation, input device to specify a viewpoint, and a conventional 2-D display to show an arbitrary viewpoint image. To generate an arbitrary viewpoint image, the Ray-Space method is used. First, the multi-view image is converted to the Ray-Space data. Then, interpolation of the Ray-Space using adaptive filter is applied. Finally, an arbitrary view image is generated from the interpolated dense Ray-Space. This paper also describes various compression methods, such as model-based compression, arbitrary-shaped DCT(Discrete Cosine Transform), VQ(Vector Quantization), and subband coding. Finally, a demonstration of a full real-time system from capturing to display is explained.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The spatial relationship of DCT coefficients between a block and its sub-blocks

Abstract: At present, almost all digital images are stored and transferred in their compressed format in which discrete cosine transform (DCT)-based compression remains one of the most important data compression techniques due to the efforts from JPEG In order to save the computation and memory cost, it is desirable to have image processing operations such as feature extraction, image indexing, and pattern classifications implemented directly in the DCT domain To this end, we present in this paper a generalized analysis of spatial relationships between the DCTs of any block and its sub-blocks The results reveal that DCT coefficients of any block can be directly obtained from the DCT coefficients of its sub-blocks and that the interblock relationship remains linear It is useful in extracting global features in the compressed domain for general image processing tasks such as those widely used in pyramid algorithms and image indexing In addition, due to the fact that the corresponding coefficient matrix of the linear combination is sparse, the computational complexity of the proposed algorithms is significantly lower than that of the existing methods

High precision encoding and decoding of video images

Abstract: Methods, systems, and computer programs for improved quality video compression. Image quality from MPEG-style video coding may be improved by preserving a higher number of bits during intermediate encoding and decoding processing steps. Problems of inverse discrete cosine transform (IDCT) mismatch can be eliminated by exactly matching the IDCT function numerical algorithm of the decoder to the IDCT function numerical algorithm used for the decoding portion of the encoder. Also included is an application of high precision compression to wide dynamic range images by extending the range of the “quantization parameter” or “QP”. The extension of QP may be accomplished either by increasing the range of QP directly, or indirectly through a non-linear transformation. Also included is an application of extended intermediate processing precision and an extended QP range to reduced contrast regions of an image to extend the precision with which the low-contrast portions are compression coded.

New semifragile image authentication watermarking techniques using random bias and nonuniform quantization

Abstract: Semi-fragile watermarking methods aim at detecting unacceptable image manipulations, while allowing acceptable manipulations such as lossy compression. In this paper, we propose new semi-fragile authentication watermarking techniques using random bias and non-uniform quantization, to improve the performance of the methods proposed by Lin and Chang. Specifically, the objective is to improve the performance tradeoff between the alteration detection sensitivity and the false detection rate.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Region of interest coding in JPEG 2000

Abstract: This paper describes the functionality in the JPEG 2000 Part 1 standard, for encoding images with predefined regions of interest (ROI) of arbitrary shape. The method described is called the Maxshift method. This method is based on scaling of the wavelet coefficients after the wavelet transformation and quantization. By sufficiently scaling the wavelet coefficients used to reconstruct the ROI, all the information pertaining to the ROI is placed before the information pertaining to the rest of the image (background), in the codestream. By varying the quantization of the image and by truncation of the codestream, different quality for the ROI and for the background can be obtained. A description is also given of how the wavelet coefficients that are used to reconstruct the ROI (ROI mask) can be found. Since the decoder uses only the number of significant bitplanes for each wavelet coefficient to determine whether it should be scaled back, an arbitrary set of wavelet coefficients can be scaled on the encoder side. This means that there is no need to encode or send the shape of the ROI. This paper also describes how this can be used to further enhance the ROI functionality. The results in this paper show that the Maxshift method can be used to greatly increase the compression efficiency by lowering the quality of the background and that it also makes it possible to receive the ROI before the background, when transmitting the image.

A SVD- and quantization based semi-fragile watermarking technique for image authentication

Abstract: With the popularity of digital images applied in journals, hospitals and courtrooms, it has become easier to modify or forge information using widely available editing software. Digital watermarking techniques have been proposed as an effective solution to the problem of image authentication. This paper presents a semi-fragile watermarking technique based on block singular value decomposition (SVD). It embeds the binary watermark image of pseudo-random permutation into the biggest singular value by quantization process. The scheme can extract the watermark without the original image. Experimental results show that the proposed scheme can prevent malicious attacks but allow JPEG lossy compression and can locate alterations made on the image.

Parallel-beam backprojection: an FPGA implementation optimized for medical imaging

Abstract: Medical image processing in general and computerized tomography (CT) in particular can benefit greatly from hardware acceleration. This application domain is marked by computationally intensive algorithms requiring the rapid processing of large amounts of data. To date, reconfigurable hardware has not been applied to this important area. For efficient implementation and maximum speedup, fixed-point implementations are required. The associated quantization errors must be carefully balanced against the requirements of the medical community. Specifically, care must be taken so that very little error is introduced compared to floating-point implementations and the visual quality of the images is not compromised. In this paper, we present an FPGA implementation of the parallel-beam backprojection algorithm used in CT for which all of these requirements are met. We explore a number of quantization issues arising in backprojection and concentrate on minimizing error while maximizing efficiency. Our implementation shows significant speedup over software versions of the same algorithm, and is more flexible than an ASIC implementation. Our FPGA implementation can easily be adapted to both medical sensors with different dynamic ranges as well as tomographic scanners employed in a wider range of application areas including nondestructive evaluation and baggage inspection in airport terminals.

Watermark Detection and Extraction Using Independent Component Analysis Method

Abstract: This paper proposes a new image watermarking technique, which adopts Independent Component Analysis (ICA) for watermark detection and extraction process (i.e., dewatermarking). Watermark embedding is performed in the spatial domain of the original image. Watermark can be successfully detected during the Principle Component Analysis (PCA) whitening stage. A nonlinear robust batch ICA algorithm, which is able to efficiently extract various temporally correlated sources from their observed linear mixtures, is used for blind watermark extraction. The evaluations illustrate the validity and good performance of the proposed watermark detection and extraction scheme based on ICA. The accuracy of watermark extraction depends on the statistical independence between the original, key and watermark images and the temporal correlation of these sources. Experimental results demonstrate that the proposed system is robust to several important image processing attacks, including some geometrical transformations—scaling, cropping and rotation, quantization, additive noise, low pass filtering, multiple marks, and collusion.

Computation reduction for motion search in low rate video coders

Abstract: In this paper, computation reduction algorithms of motion estimation are developed for low rate video coders. By jointly considering motion estimation, discrete cosine transform, and quantization, the all-zero and zero-motion detection algorithms are suggested to reduce the computation of motion estimation. Simulation results show that many unnecessary computations in motion estimation are greatly reduced. For the Akiyo sequence, the proposed algorithms reduce the average numbers of search points from 28.90 and 4.99 to 2.89 and 1.40 for three-step search and diamond-search algorithms, respectively.

JPEG 2000 and Region of Interest Coding

Abstract: This paper details work undertaken on the application of JPEG 2000, the recent ISO/ITU-T image compression standard based on wavelet technology, to region of interest (ROI) coding. The paper briefly outlines the JPEG 2000 encoding algorithm and explains how the packet structure of the JPEG 2000 bit-stream enables an encoded image to be decoded in a variety of ways dependent upon the application. The three methods by which ROI coding can be achieved in JPEG 2000 (tiling; coefficient scaling; and codeblock selection) are then outlined and their relative performance empirically investigated. The experimental results show that there are a number of parameters that control the effectiveness of ROI coding, the most important being the size and number of regions of interest, code-block size, and target bit rate. Finally, some initial results are presented on the application of ROI coding to face images.

A de-blocking algorithm and a blockiness metric for highly compressed images

Abstract: Blockiness is a typical artifact in reconstructed images that have been coded by a block-based discrete cosine transform (BDCT). In highly compressed images and video, the blocking artifacts are easily noticeable as the discontinuities between relatively homogeneous regions. Many current noniterative de-blocking algorithms attempt to remove the blocking artifacts by smoothing a few pixels around the block boundaries; however, the results are not satisfactory, especially at very low bit rates. We propose a de-blocking algorithm based on the number of connected blocks in a relatively homogeneous region, the magnitude of abrupt changes between neighboring blocks, and the quantization step size of DCT coefficients. Due to its adaptability, the proposed algorithm can smooth out the blocking artifacts while keeping the strong edges and texture areas untouched. Since this algorithm is noniterative and only identifies those block pairs that actually need de-blocking, its computation cost is low. In addition, we have developed a new metric to measure the blocking artifacts in images. Through analyzing the 2N-point (N is the block size) one-dimensional DCT coefficients of the two neighboring blocks with blocking artifacts, we show that all of the even DCT coefficients of the combined 2N points are zeros (except frequency k=0). The odd DCT coefficients are proportional to the pixel value difference between these two blocks with their magnitudes almost inversely proportional to frequency k. We selected the first DCT coefficient (frequency k=1) as an indicator for the strength of blocking artifacts in the reconstructed images. For the postprocessed images, we used a weighted summation of the squared first DCT coefficient to measure their blocking artifacts. Experimental results demonstrate that our proposed de-blocking algorithm produces better results than other methods, both visually and quantitatively, while the proposed blocking artifact metric is more consistent with subjective evaluation than the peak signal-to-noise ratio.

Adaptive approximate nearest neighbor search for fractal image compression

Abstract: Fractal image encoding is a computationally intensive method of compression due to its need to find the best match between image subblocks by repeatedly searching a large virtual codebook constructed from the image under compression. One of the most innovative and promising approaches to speed up the encoding is to convert the range-domain block matching problem to a nearest neighbor search problem. This paper presents an improved formulation of approximate nearest neighbor search based on orthogonal projection and pre-quantization of the fractal transform parameters. Furthermore, an optimal adaptive scheme is derived for the approximate search parameter to further enhance the performance of the new algorithm. Experimental results showed that our new technique is able to improve both the fidelity and compression ratio, while significantly reduce memory requirement and encoding time.

Medical image compression by sampling DCT coefficients

Abstract: Advanced medical imaging requires storage of large quantities of digitized clinical data. Due to the constrained bandwidth and storage capacity, however, a medical image must be compressed before transmission and storage. Among the existing compression schemes, transform coding is one of the most effective strategies. Image data in the spatial domain is transformed into the spectral domain after the transformation to attain more compression gains. Based on the quantization strategy, coefficients of low amplitude in the transformed domain are discarded and significant coefficients are preserved to increase the compression ratio without inducing salient distortion. We use an adaptive sampling algorithm by calculating the difference area between correct points and predicted points to decide the significant coefficients. Recording or transmitting the significant coefficients instead of the whole coefficients achieves the goal of compression. On the decoder side, a linear equation is employed to reconstruct the coefficients between two sequent significant coefficients. Simulations are carried out to different medical images, which include sonogram, angiogram, computed tomography, and X-ray images.

Blind quality assessment for JPEG2000 compressed images

Abstract: Measurement of image quality is crucial for many image-processing algorithms, such as acquisition, compression, restoration, enhancement and reproduction. Traditionally, image quality assessment algorithms have focused on measuring image fidelity, where quality is measured as fidelity with respect to a 'reference' or 'perfect' image. The field of blind quality assessment has been largely unexplored. In this paper we present an algorithm for blindly determining the quality of JPEG2000 compressed images. Our algorithm assigns quality scores that are in good agreement with human evaluations. Our algorithm utilizes a statistical model for wavelet coefficients and computes features that exploit the fact that quantization produces more zero coefficients than expected for natural images. The algorithm is trained and tested on data obtained from human observers, and performs close to the limit on useful prediction imposed by the variability between human subjects.

Method and decoder system for reducing quantization effects of a decoded image

Abstract: A method (200) and decoder system (100) for reducing quantization effects or ringing artifacts imposed upon decoded image of hybrid block based coding schemes such as MEPG and H 261. The system (100),and method (200: receive (220) decoded image decoded blocks that were decoded from transform coded blocks quatized by a selected quantization parameter; analyze (230) selected pixel values of selected pixels with neighboring pixel values of associated neighboring pixels in the decoded blocks to determine difference values for each of the selected pixels; and detect (240) potential object edges, to identify the selected pixels as edge pixels. The selected pixel values are modified (250) if they are not identified as edge pixels.

Rate-distortion optimized image compression using wedgelets

Abstract: Most wavelet-based image coders fail to model the joint coherent behavior of wavelet coefficients near edges. Wedgelets offer a convenient parameterization for the edges in an image, but they have yet to yield a viable compression algorithm. In this paper, we propose an extension of the zerotree-based space-frequency quantization (SFQ) algorithm by adding a wedgelet symbol to its tree-pruning optimization. This incorporates wedgelets into a rate-distortion compression framework and allows simple, coherent descriptions of the wavelet coefficients near edges. The resulting method yields improved visual quality and increased compression efficiency over the standard SFQ technique.

Multiframe resolution-enhancement methods for compressed video

Abstract: Multiframe resolution enhancement ("superresolution") methods are becoming widely studied, but only a few procedures have been developed to work with compressed video, despite the fact that compression is a standard component of most image- and video-processing applications. One of these methods uses quantization-bound information to define convex sets and then employs a technique called "projections onto convex sets" (POCS) to estimate the original image. Another uses a discrete cosine transformation (DCT)-domain Bayesian estimator to enhance resolution in the presence of both quantization and additive noise. The latter approach is also capable of incorporating known source statistics and other reconstruction constraints to impose blocking artifact reduction and edge enhancement as part of the solution. We propose a spatial-domain Bayesian estimator that has advantages over both of these approaches.

Wavelet-based digital watermarking for image authentication

Abstract: We present a novel watermarking scheme to ensure the credibility of digital images. The proposed technique is able to detect malicious tampering of images even if they have been incidentally distorted by basic image processing operations. Our system is based on the quantization of wavelet packet coefficients and uses characteristics of the human visual system to maximize the embedding weights while keeping good perceptual transparency. We develop an image-dependant method to evaluate, in the discrete wavelet domain, the optimal quantization steps allowing the tamper proofing of still images. The nature of multiresolution discrete wavelet decomposition allows the spatial and frequency localization of image tampering. Experimental results are presented to demonstrate the capacity of our system to detect unauthorized modification of images while staying robust to image compression.

A DWT-based color image steganography scheme

Abstract: A novel text cryptosystem is proposed. The secret information is hidden into a publicly accessed color image by a quantization-based strategy, so the transportation of the secret information will not attract the attention of illegal eavesdropper. With our approach, the secret information is embedded in the wavelet domain of every chrominance component, so the hiding capacity is larger than the similar steganography software. The embedded sequence can be reliably extracted without resorting to the original image. Simulation results show that the proposed method is robust against commonly used image processing techniques.

Blind image watermarking via derivation and quantization of robust semi-global statistics

Abstract: We introduce a new approach for blind image watermarking: We derive robust semi-global features in wavelet domain and quantize them in order to embed the watermark. Quantization of statistics is carried out by adding scaled pseudo-random sequences that are visually unnoticeable. Our algorithm exhibits increased robustness against various attacks and it withstands standard benchmark attacks of wider trange than earlier methods (e.g., Stirmark, random bending etc.) and modifications such as compression, provided they do not cause too severe visual distortions.

System and method for authentication of JPEG image data

Abstract: A system and method for authentication of JPEG image data enables the recipient to ascertain whether the received image file originated from a known identified source or whether the contents of the file have been altered in some fashion prior to receipt. A unique hashing function is derived from a first section of image data contained in the JPEG compressed image in such a way that any changes subsequently made to the first section of image data is reflected in a different hashing function being derived from a signature string is embedded into a next section of the image data. Since the embedding of a previous section's integrity checking number is done without modifying the JPEG bit stream, any JPEG decoder can thereafter properly decode the image.

A Method of Embedding Binary Data into JPEG Bitstreams

Abstract: This paper considers irreversible coding by JPEG, and proposes a method of embedding binary data into the image. The proposed method embeds the information into the AC coefficients after quantization. The information is embedded in the AC coefficients of higher frequency, and by setting the quantization table corresponding to these AC coefficients to small values, visual image degradation is limited. In the proposed method, the embedded information is completely recovered in decoding, leaving little effect on the image after recovering the information. The coded sequence can be decoded using a conventional JPEG decoder, even in an environment where the information is not to be recovered or cannot be recovered. The method is designed so that image degradation is also limited in such a case. © 2001 Scripta Technica, Syst Comp Jpn, 33(1): 18–26, 2002

Fixed pattern noise compensation with low memory requirements

Abstract: A method and a system for the compensation of Fixed Pattern Noise (FPN) in digital images have been achieved. The FPN compensation is based on processing done during the production of said images. The fixed pattern noise is here defined as the fixed pattern seen in the individual pixel offsets. The fixed pattern noise is uncorrelated noise but it has a statistical distribution that can be scaled to fit all images. The general idea is to measure the distribution for each individual camera, compress it, and save it in the module. For each image that is then taken with the module the noise pattern can be retrieved and rescaled to fit the image. Covered pixels are employed to normalize the FPN data to the current frame. In order to minimize memory requirements a compression scheme has to be used. A method combining a quantization step with a non-lossy compression is used. The black level is corrected for as part of the operation.

Morphological representation of DCT coefficients for image compression

Abstract: Recent success in discrete cosine transform (DCT) image coding is mainly attributed to recognition of the importance of data organization and representation. Currently, there are several competitive DCT-based coders such as DCT-based embedded image coding (EZDCT) (see Xiong et al., Z., 1996) and significance tree quantization (STQ) (see Davis, G. and Chawla, S., 1997). In the wavelet context, morphological representation of wavelet data has achieved the best compression performance. The representatives are morphological representation of wavelet data (MRWD) (see Servetto, S. et al., 1999) and significance-linked connected component analysis (see Chai, B.-B. et al., 1999). We show that, by proper reorganization of its coefficients, the block-based DCT can have similar characteristics, such as energy compaction, cross-subband similarity, decay of magnitude across subband, etc., to the wavelet transform. These characteristics can widen DCT applications relevant to image compression, image retrieval, pattern recognition, etc. We then present an image coder utilizing these characteristics by morphological representation of DCT coefficients (MRDCT). The experiments show that MRDCT is among the state-of-the-art DCT-based image coders reported in the literature. For example, for the Lena image at 0.25 bpp, MRDCT outperforms JPEG, STQ and EZDCT in peak signal-to-noise ratio by 1.0, 1.0, and 0.3 dB, respectively.

Cache-efficient wavelet lifting in JPEG 2000

Abstract: The discrete wavelet transform (DWT), the technology at the heart of the JPEG 2000 image compression system, operates on user-definable tiles of the image, as opposed to fixed-size blocks of the image as does the discrete cosine transform (DCT) used in JPEG. This difference reduces artificial blocking effects but can severely stress the memory system. We examine the interaction of the DWT and the memory hierarchy, modify the structure of the DWT computation and the layout of the image data to improve cache and translation lookaside buffer (TLB) locality, and demonstrate significant performance improvements of the DWT over a baseline implementation. Our optimized DWT implementation exhibits speedups of up to 4/spl times/ over the DWT in a JPEG 2000 reference implementation.

Color image process method and apparatus thereof

Abstract: A color image processing apparatus which codes image data while suppressing image deterioration. A color character area discrimination unit divides an input color image into 16x16-pixel blocks, and determines whether or not each block expresses color characters. In accordance with the determination result, a sub-sampling ratio switching unit switches the sampling ratio for each of color components YCrCb composing the color image data so that the sample ratio is Y:Cr:Cb=4:2:2 or Y:Cr:Cb=4:1:1. Subsequently, sampling is performed in accordance with the switched sampling ratio, and DCT, linear quantization and entropy coding are then performed.