Showing papers on "Quantization (image processing) published in 1994"

Image Compression Using the Discrete Cosine Transform

Abstract: The discrete cosine transform (DCT) is a technique for converting a signal into elementary frequency components. It is widely used in image compression. Here we develop some simple functions to compute the DCT and to compress images. These functions illustrate the power of Mathematica in the prototyping of image processing algorithms. The rapid growth of digital imaging applications, including desktop publishing, multimedia, teleconferencing, and high-definition television (HDTV) has increased the need for effective and standardized image compression techniques. Among the emerging standards are JPEG, for compression of still images [Wallace 1991]; MPEG, for compression of motion video [Puri 1992]; and CCITT H.261 (also known as Px64), for compression of video telephony and teleconferencing. All three of these standards employ a basic technique known as the discrete cosine transform (DCT). Developed by Ahmed, Natarajan, and Rao [1974], the DCT is a close relative of the discrete Fourier transform (DFT). Its application to image compression was pioneered by Chen and Pratt [1984]. In this article, I will develop some simple functions to compute the DCT and show how it is used for image compression. We have used these functions in our laboratory to explore methods of optimizing image compression for the human viewer, using information about the human visual system [Watson 1993]. The goal of this paper is to illustrate the use of Mathematica in image processing and to provide the reader with the basic tools for further exploration of this subject.

Data compression and decompression

Abstract: A compression and decompression method uses a wavelet decompositin, frequency based tree encoding, tree based motion encoding, frequency weighted quantization, Huffman encoding, and/or tree based activity estimation for bit rate control. Forward and inverse quasi-perfect reconstruction transforms are used to generate the wavelet decomposition and to reconstruct data values close to the original data values. The forward and inverse quasi-perfect reconstruction transforms utilize special filters at the boundaries of the data being transformed and/or inverse transformed. Structures and methods are disclosed for traversing wavelet decompositions. Methods are disclosed for increasing software execution speed in the decompression of video. Fixed or variable length tokens are included in a compressed data stream to indicate changes in encoding methods used to generate the compressed data stream.

Method and apparatus for reducing quantization artifacts in a hierarchical image storage and retrieval system

Abstract: The system and method reduces the quantization artifacts in the addition and removal of a digital watermark to and from a selected resolution image of a hierarchical image storage system where the watermark removal record is placed in a higher resolution image component. For those applications where preserving the image quality of a higher resolution image component is more critical than preserving the image quality of a lower resolution image component, the low-resolution image is modified according to the teachings of the present invention to minimize and in many cases eliminate the quantization artifacts at the higher resolution component.

Rate-distortion optimal fast thresholding with complete JPEG/MPEG decoder compatibility

Abstract: We show a rate-distortion optimal way to threshold or drop the DCT coefficients of the JPEG and MPEG compression standards. Our optimal algorithm uses a fast dynamic programming recursive structure. The primary advantage of our approach lies in its complete compatibility with standard JPEG and MPEG decoders. >

Compression of Digital Images by Block Truncation Coding: A Survey

Abstract: Block truncation coding (BTC) is a lossy moment preserving quantization method for compressing digital gray-level images. Its advantages are simplicity, fault tolerance, the relatively high compression efficiency and good image quality of the decoded image. Several improvements of the basic method have been recently proposed in the literature. In this survey we will study the basic algorithm and its improvements by dividing it into three separate tasks; performing quantization, coding the quantization data and cling the bit plane. Each phase of the algorithm will be analyzed separately. On the basis of the analysis, a combined BTC algorithm will be proposed and the comparisons to the standard JPEG algoritbm will be made

Perceptual optimization of DCT color quantization matrices

Abstract: The JPEG baseline standard for image compression employs a block discrete cosine transform (DCT) and uniform quantization. For a monochrome image, a single quantization matrix is allowed, while for a color image, distinct matrices are allowed for each color channel. We describe a method, called DCTune, for the design of color quantization matrices that is based on a model of the visibility of quantization artifacts. The model describes the artifact visibility as a function of DCT frequency, color channel, and display resolution and brightness. The model also describes the summation of artifacts over space and frequency, and masking of artifacts by the image itself. The DCTune matrices are different from the de facto JPEG matrices, and appear to provide superior visual quality at equal bit-rates. >

An improvement on codebook search for vector quantization

Abstract: Presents a simple but effective algorithm to speed up the codebook search in a vector quantization scheme when a MSE criterion is used. A considerable reduction in the number of operations is achieved. This algorithm was originally designed for image vector quantization in which the samples of the image signal (pixels) are positive, although it can be used with any positive-negative signal with only minor modifications. >

On the distribution of the DCT coefficients

Abstract: The paper presents a statistical study in order to improve the image compression rate in discrete cosine transform (DCT) based methods and especially for compression methods which are defined in JPEG norm. It is realised extensively, using a battery of parametric and non-parametric fit-tests and laws such as those of Cauchy, Laplace, Gauss, and a mixture distribution of Laplace and Gaussian. Considering the absence of results for these laws in the literature, the authors constructed adapted statistical tools for DCT coefficients analysis. Then, they show that these coefficients can be modelized by a Gaussian finite mixture distribution. They also comment on the obtained results for medical images applications and explain how the compression rate can be improve with them. >

Post-filtering for decoded video signals

Abstract: Encoded video signals comprise sets of transform coefficients (e.g., DCT coefficients) corresponding to different regions of a video frame. An inverse transform is applied to sets of transform coefficients to generate decoded regions of a decoded video frame. The discontinuities for boundaries between adjacent regions are used to adjust one or more of the transform coefficients. The adjusted sets of transform coefficients are then used to generate filtered regions of a filtered video frame corresponding to the decoded video frame. In a preferred embodiment, the transform coefficients are DCT coefficients and the DC and first two AC DCT coefficients are sequentially adjusted to correct for quantization errors in the encoding process.

Fractal (self-VQ) encoding of video sequences

Abstract: We present results of a scheme to encode video sequences of digital image data based on a quadtree still-image fractal method. The scheme encodes each frame using image pieces, or vectors, from its predecessor; hence it can be thought of as a VQ scheme in which the code book is derived from the previous image. We present results showing: near real-time (5 - 12 frames/sec) software-only decoding; resolution independence; high compression ratios (25 - 244:1); and low compression times (2.4 - 66 sec/frame) as compared with standard fixed image fractal schemes.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Color image quantization by agglomerative clustering

Abstract: We present a simple and "well-behaved" agglomerative clustering approach to color image quantization, along with results of tests using synthesized and real-life images. >

Jpeg/mpeg decoder-compatible optimized thresholding for image and video signal compression

Abstract: For encoding signals corresponding to still images or video sequences, respective standards known as JPEG and MPEG have been proposed These standards are based on digital cosine transform (DCT) compression For economy of transmission, DCT coefficients may be "thresholded" prior to transmission, by dropping the less significant DCT coefficients While maintaining JPEG or MPEG compatibility, threshold selection for the DCT coefficients of an image or video frame is based on optimizing for minimum distortion for a specified maximum target coding bit rate or, equivalently, for minimized coding bit rate for a specified maximum allowable distortion constraint In the selection process, a dynamic programming method is used

Image coding by use of discrete cosine transforms

Abstract: Image coding methods and apparatus employing discrete cosine transforms for supressing and/or reducing blocking artifacts using a JPEG file format. The methods can be implemented on JPEG hardware slightly modified to provide access to discrete cosine transform coefficients. Filtering techniques by which an overlap procedure for implementing the inventive methods are also disclosed.

Perceptual based color-compression for raster image quantization

Abstract: A method and apparatus for performing color compression uses human factors to weight a distance metric in order to select a set of k presentation colors to represent n colors in an original image, where n>k. This same distance metric is used as part of a process to select an optimal mapping of the original image pixels to the presentation colors. The presentation colors are selected based upon a data clustering scheme in which clusters of colors are selected based upon their respective distance from each color within a given cluster and from colors in other clusters. Colors in different clusters are required to be farther apart than colors in the same clusters. This accounts for colors with high importance in accurately presenting the presentation image but having low overall occurrence in the image file.

Image signal processing device

Abstract: An image signal processing device generates first image data and second image data based on the same optical image. Each pixel of the second image data is offset from the corresponding pixel of the first image data by half the distance between the centers of two adjacent pixels. The first image data is then subjected to a discrete cosine transformation (DCT), quantization, and Huffman encoding, and is recorded to an IC memory card. High resolution image data is generated based on the first and second image data. Expanded image data is obtained based on the first image data, and supplementary data is generated based on the high resolution image data and the expanded image data. The supplementary data is subjected to DCT, quantization and Huffman encoding, and is recorded to the same IC memory card.

Image sensor and electronic still camera with an addressable image pickup section and an analog product sum calculation section

Abstract: An electronic still camera wherein an image compression circuit can be simplified includes a lens system, a shutter, an image sensor and a processing circuit. A video signal for one frame outputted from the processing circuit in response to a shutter operation is written into a memory. A video signal read out from the memory is compressed in accordance with the JPEG system by an image compression circuit and then written into a memory card. The image sensor is constituted from an image pickup section and a product sum calculation section. A CMD image sensor capable of non-destructively reading out a picture signal is used as the image pickup section. The product sum calculation section performs DCT processing required for compression processing of the JPEG system. Since a detected image signal processed by DCT processing is obtained from the image sensor, DCT processing of the image compression circuit is unnecessary.

Error resilient pyramid vector quantization for image compression

Abstract: The robustness of image and video compression in the presence of time-varying channel error has received increased interest with the emergence of portable digital receivers and computers. To achieve robust compression, pyramid vector quantization (PVQ) can be used. It is a fixed-rate quantization scheme suited to Laplacian-like sources, such as those arising from transform and subband image coding. The authors propose a new method of PVQ which not only improves upon the image compression performance of typical JPEG implementations, but also demonstrates excellent resilience to channel error. >

JPEG decompression with reduced artifacts

Abstract: The major artifacts of JPEG compressed images are blocking and ringing, which are mainly due to the quantization of low frequency and high frequency DCT components respectively. The ringing artifacts are particularly dominant in document images, where sharp edges present commonly in text and graphics are more likely to be encountered. In this paper we describe a decompression algorithm with reduction in both ringing and blocking artifacts.

Improved techniques for single-pass adaptive vector quantization : Data compression

Abstract: Constantinescu and Storer [4], present a new single-pass adaptive vector quantization algorithms that learns a condebook of variable size and shape entries; they present experiments on a set of test images showing that with no training or prior knowledge of the data, for a given fidelity, the compression achieved typically equals or exceeds that of the JPEG standard

Fast software processing of motion JPEG video

Abstract: This paper introduces a set of techniques for processing video data compressed using JPEG compression at near real-time rates on current generation workstations. Performance is improved over traditional methods by processing video data in compressed form, avoiding compression and decompression and reducing the amount of data processed. An approximation technique called condensation is developed that further reduces the complexity of the operation. The class of operations that are computable using the techniques developed in this paper are called linear, global digital specials effects (LGDSEs), and represent those effects where a pixel in the output image is a linear combination of pixels in the input image. Many important video processing problems, including convolution, scaling, rotation, translation, and transcoding can be expressed as LGDSEs.

Processing image sequences based on eye movements

Abstract: Subjects rated the subjective image quality of video sequences that were processed using gaze- contingent techniques. Gaze-contingent processing was implemented by adaptively varying image quality within each video field such that image quality was maximal in the region most likely to be viewed and was reduced in the periphery. This was accomplished by blurring the image or by introducing quantization artifacts. Results showed that provision of a gaze- contingent, high-resolution region had a modest beneficial effect on perceived image quality, compared to having a high-resolution region that was not gaze-contingent. Given the modest benefits and high cost of implementation, we conclude that gaze-contingent processing is not suitable for general purpose image processing.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Image compression using fractals and discrete cosine transform

Abstract: A new image data compression method using both fractals and the discrete cosine transform (DCT) is presented. The original image is first encoded by fractals in the DCT domain, then the error image is encoded using the DCT. Experiments show that the method can achieve high fidelity at a high compression ratio.

Set theoretic compression with an application to image coding

Abstract: We discuss the concept of set theoretic compression where the input signal is implicitly encoded by the specification of a set which contains it, rather than an estimate which approximates it. This approach assumes the reconstruction of an estimate from the encoded set information only at the decoder side. We explain the motivations of this approach for high signal compression and encoding simplification, and the implication of more complex decoding. We then present the tools to support the approach. We finally show a demonstration of this approach in a particular application of image coding. >

Optimization techniques for adaptive quantization of image and video under delay constraints

Abstract: Optimization techniques for adaptive quantization of image and video under delay constraints Antonio Ortega Traditionally, rate-distortion (R-D) theory has been concerned with providing bounds on the optimal performance for various classes of coding algorithms and sources. In this thesis we depart from that approach in two ways. First, our objective are operational R-D results, i.e. we study algorithms that can nd the optimal solution for a given coder con guration and known inputs, without relying on modeling either the encoder or the source. Second, we seek to explore explicitly other parameters that determine the achievable R-D performance, namely, the encoding delay and complexity, and the memory at the encoder. We compute the optimal solution even if it requires too much complexity, memory or delay to be considered in a practical setting. Optimal schemes serve as a benchmark and can also be the basis for heuristic methods which provide slightly suboptimal but more e cient performance. More speci cally we study the following topics: (i) Optimal bu er constrained quantization. We nd optimal solutions for the bu er control problem in a deterministic framework by assuming a long encoding delay. Our solution, based on dynamic programming, also leads us to short delay, lower complexity heuristics. (ii) Rate control and policing constraints for video transmission over ATM networks. We study the problem of optimizing the source quality as in (i), while taking into account network considerations. (iii) Optimization of dependent quantization environments. Optimal bit allocation results are presented for dependent quantization schemes (e.g. DPCM, predictive motion compensated video coding, MPEG). (iv) Rate-delay trade-o s in a multiresolution image database system. We study how the bit allocation in a multiresolution coding system can be chosen so as to minimize the end-to-end query delay in browsing through a set of images. (v) Adaptive quantization without side information. We propose a backward adaptive quantization algorithm where the input distribution is \learned" from past quantized samples. This allows adaptation to sources with unknown or time-varying input distribution. List of Abbreviations ATM Asynchronous Transfer Mode B Bidirectionally interpolated mode (in MPEG) CBR Constant Bit Rate DCT Discrete Cosine Transform DP Dynamic Programming DPCM Di erential Pulse Coded Modulation GAP Generalized Assignment Problem HDTV High De nition Television HVS Human Visual System I Intraframe mode (in MPEG) JPEG Joint Photographic Experts Group KLT Karhunen Lo eve Transform LB Leaky Bucket MPEG Moving Pictures Experts Group MR Multiresolution MSE Mean Squared Error P Prediction mode (in MPEG) PSNR Peak Signal to Noise Ratio R-D Rate{Distortion SBC Subband Coding SMG Statistical Multiplexing Gain

Image coding method and apparatus therefor

Abstract: An image coding method includes the steps of producing a complexity normalizing signal for respective macro blocks based on a complexity in a space domain with regard to an input image, producing a zero coefficient sum by performing a discrete cosine transform operation on the input image and counting the discrete cosine transform coefficients from -1 to +1, producing a zero coefficient normalizing value for respective macro blocks in accordance with the zero coefficient sum; producing a transient weight signal for respective macro blocks in accordance with the zero coefficient sum and a predetermined compression ratio, and summing the complexity normalizing signal, the zero coefficient normalizing value and the transient weight signal so as to produce the scale factor. The quantization step size of the discrete cosine transform coefficients is controlled in a macro block in accordance with the scale factor. Thus, image frames having various complexities can be encoded at a constant bit rate with no deterioration of the image.

Compression of gray-scale fingerprint images

Abstract: The FBI has developed a specification for the compression of gray-scale fingerprint images to support paperless identification services within the criminal justice community. The algorithm is based on a scalar quantization of a discrete wavelet transform decomposition of the images, followed by zero run encoding and Huffman encoding.

Facsimile with user selective compression methods

Abstract: An apparatus having the G4 method and the JPEG method allows for the selection of standard resolution (200 dpi×200 dp) or precision resolution (400 dpi×400 dpi) by using a resolution selection key of operation unit 26 in order to improve the operativity and extend the breadth of selection of image quality. For each selection of standard resolution or precision resolution, the resolution and code information for designating quantization table for use with JPEG are stored in RAM 16, with its memory area being backed up by a battery.

A model for JPEG quantization

Abstract: Presents a strategy for generating optimal JPEG quantization tables to approximate a target compression ratio. This uses a model to express the quantization coefficients as functions of compression ratio and their position in the quantization table. Simulated annealing of model parameters was used to find optimum models for an image which is a composite of several standard test images. Models of varying complexity with 1 to 6 parameters were optimized at three compression ratios, and a three parameter model was chosen to represent quantization tables. After further optimizations over a range of compressions, a general model was obtained by expressing each model parameter as a function of the compression. Application to three CCITT test pictures demonstrates the quality of recovered images. >

A fast picture compression technique

Abstract: One of the most efficient image compression techniques investigated is the discrete cosine transform (DCT). The authors present a method where, through the use of pruning, the speed of implementation of the algorithm is dramatically increased. They describe its use in image compression. The advantage of the pruning algorithm in such cases being that, only a small proportion of the DCT values are retained hence why calculate the values which are not retained. Results show that for an 8 by 8 image block it is only necessary to calculate a 4 by 4 subset of the DCT values to retain an acceptable image quality, this gives a considerable speedup in calculation time compared with calculating the full 8 by 8 DCT block. Another advantage of the technique is that parallelisation can be achieved using the data partitioning method. For the JPEG standard, the image is split into 8 by 8 blocks and the DCT of each block calculated, each block is independent of its neighbours and hence can be calculated in parallel, as with all parallel applications data transfer times are crucial, here the pruning algorithm has a second advantage in that only a subset of the results of the DCT need be transferred back to the root process. Results are presented for its application to the JPEG standard. They discuss both the effects of pruning on the image quality and the effects of pruning on parallelisation and speedup. >

Elimination of subband-coding artifacts using the dithering technique

Abstract: Subband image coding produces several types of artifacts, including contouring and ringing. We use the dithering technique to remove these artifacts. By dithering the subband signals, we can replace signal-dependent artifacts with signal-independent white noise which is less annoying to human eyes. The subjective quality of the coded images is hence improved. In addition, signal-independent white noise can be easily removed by existing noise-reduction methods. The dithering technique can also be applied to transform coding, including the discrete cosine transform, to remove the blocking artifact. Experiment results that illustrate the effectiveness of dithering are given. >