Showing papers on "Quantization (image processing) published in 1992"

The JPEG still picture compression standard

Abstract: A joint ISO/CCITT committee known as JPEG (Joint Photographic Experts Group) has been working to establish the first international compression standard for continuous-tone still images, both grayscale and color. JPEG's proposed standard aims to be generic, to support a wide variety of applications for continuous-tone images. To meet the differing needs of many applications, the JPEG standard includes two basic compression methods, each with various modes of operation. A DCT (discrete cosine transform)-based method is specified for 'lossy' compression, and a predictive method for 'lossless' compression. JPEG features a simple lossy technique known as the Baseline method, a subset of the other DCT-based modes of operation. The Baseline method has been by far the most widely implemented JPEG method to date, and is sufficient in its own right for a large number of applications. The author provides an overview of the JPEG standard, and focuses in detail on the Baseline method. >

JPEG: Still Image Data Compression Standard

Abstract: Foreword. Acknowledgments. Trademarks. Introduction. Image Concepts and Vocabulary. Aspects of the Human Visual Systems. The Discrete Cosine Transform (DCT). Image Compression Systems. JPEG Modes of Operation. JPEG Syntax and Data Organization. Entropy Coding Concepts. JPEG Binary Arithmetic Coding. JPEG Coding Models. JPEG Huffman Entropy Coding. Arithmetic Coding Statistical. More on Arithmetic Coding. Probability Estimation. Compression Performance. JPEG Enhancements. JPEG Applications and Vendors. Overview of CCITT, ISO, and IEC. History of JPEG. Other Image Compression Standards. Possible Future JPEG Directions. Appendix A. Appendix B. References. Index.

Determining optical flow

Abstract: Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components A second constraint is needed A method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences The algorithm is robust in that it can handle image sequences that are quantified rather coarsely in space and time It is also insensitive to quantization of brightness levels and additive noise Examples are included where the assumption of smoothness is violated at singular points or along lines in the image

Iterative procedures for reduction of blocking effects in transform image coding

Abstract: The authors propose an iterative block reduction technique based on the theory of a projection onto convex sets. The idea is to impose a number of constraints on the coded image in such a way as to restore it to its original artifact-free form. One such constraint can be derived by exploiting the fact that the transform-coded image suffering from blocking effects contains high-frequency vertical and horizontal artifacts corresponding to vertical and horizontal discontinuities across boundaries of neighboring blocks. Another constraint has to be with the quantization intervals of the transform coefficients. Specifically, the decision levels associated with transform coefficient quantizers can be used as lower and upper bounds on transform coefficients, which in turn define boundaries of the convex set for projection. A few examples of the proposed approach are presented. >

Fast algorithms for the discrete cosine transform

Abstract: Several fast algorithms for computing discrete cosine transforms (DCTs) and their inverses on multidimensional inputs of sizes which are powers of 2 are introduced. Because the 1-D 8-point DCT and the 2-D 8*8-point DCT are so widely used, they are discussed in detail. Algorithms for computing scaled DCTs and their inverses are also presented. These have applications in compression of continuous tone image data, where the DCT is generally followed by scaling and quantization. >

A motion video compression system with adaptive bit allocation and quantization

Abstract: A system and method are disclosed for implementing an encoder suitable for use with the proposed ISO/IEC MPEG standards including three cooperating components or subsystems that operate to variously adaptively pre-process the incoming digital motion video sequences, allocate bits to the pictures in a sequence, and adaptively quantize transform coefficients in different regions of a picture in a video sequence so as to provide optimal visual quality given the number of bits allocated to that picture.

Luminance-model-based DCT quantization for color image compression

Abstract: A model is developed to approximate visibility thresholds for discrete cosine transform (DCT) coefficient quantization error based on the peak-to-peak luminance of the error image. Experimentally measured visibility thresholds for R, G, and B DCT basis functions can be predicted by a simple luminance-based detection model. This model allows DCT coefficient quantization matrices to be designed for display conditions other than those of the experimental measurements: other display luminances, other veiling luminances, and other spatial frequencies (different pixel spacings, viewing distances, and aspect ratios).

Method for finding a most likely matching of a target facial image in a data base of facial images

Abstract: A method of finding a most likely match for a target facial image within a data base of stored facial images comprising determining a score for each data base image as a function of closeness of a quantization of selected facial features between each data base image and the target image and ordering the data base for sequential processing according to the potential value score in descending order, sequentially processing each data base image starting from the highest potential value score by an image comparison process to establish a correlation score for each comparison, and applying one or more decision rules to each comparison to reach a decision.

Fast full search equivalent encoding algorithms for image compression using vector quantization

Abstract: Three fast search routines to be used in the encoding phase of vector quantization (VQ) image compression systems are presented. These routines, which are based on geometric considerations, provide the same results as an exhaustive (or full) search. Examples show that the proposed algorithms need only 3-20% of the number of mathematical operations required by a full search and fewer than 50% of the operations required by recently proposed alternatives. >

An embedded wavelet hierarchical image coder

Abstract: A simple, yet remarkably effective, image compression algorithm that has the property that the bits in the bit stream are generated in order of importance, yielding fully hierarchical image compression suitable for embedded coding or progressive transmission, is described. Given an image bit stream, the decoder can cease decoding at the same image that would have been encoded at the bit rate corresponding to the truncated bit stream. The compression algorithm is based on three key concepts: (1) wavelet transform or hierarchical subband decomposition, (2) prediction of the absence of significant information across scales by exploiting the self-similarity inherent in images, and (3) hierarchical entropy-coded quantization. >

Partitioning tree image representation and generation from 3D geometric models

Abstract: While almost all research on image representation has assumed an underlying discrete space, the most common sources of images have the structure of the continuum. Although employing discrete space representations leads to simple algorithms, among its costs are quantization errors, significant verbosity and lack of structural information. A neglected alternative is the use of continuous space representations. In this paper we discuss one such representation and algorithms for its generation from views of 3D continuous space geometric models. For this we use binary, space partitioning trees for representing both the model and the image. Our approach falls under the general rubric of visible surface algorithms, providing an objectspace algorithm which under certain conditions requires only sub-linear time for a partitioning tree represented model, and in general exploits occlusion so that the computational cost converges toward the complexity of the image as the depth complexity increases. Visible edges can also be generated as a step following visible surface determination. However, an important contextual difference is that the resulting image trees are used in subsequent continuous space operations. These include affine transformations, set operations, and metric calculations, which can be used to provide image compositing, incremental image modification in a sequence of frames, and facilitating matching for computer vision/robotics. Image trees can also be used with the hemicube and light buffer illumination methods as a replacement for regular grids, thereby providing exact rather than approximate visibility. Discrete vs. Continuous Space We have come to think of images as synonymous with a 2D array of pixels. However, this is an artifact of the transducers we use to convert between the physical domain and the informational domain. Physical space at the resolution with which we are concerned is most effectively modeled mathematically as being continuous; that is, as having the structure of the Reals (or at least the Rationals) as opposed to the structure of the Integers. Modeling space as being defined on a regular lattice, while simple, is verbose and induces quantization which reduces accuracy and can introduce visible artifacts. Using nothing other than a lattice for the representation provides no image dependent structure such as edges. Consider applying to a discrete image an affine transformation, an elementary spatial operation. The solution for this is developed by reasoning not merely in discrete space but in the continuous domain as well: samples are used to reconstruct a "virtual" continuous function which is then resampled. However, the quantization effects can become rather apparent should the transform entail a significant increase in size and a rotation by some small angle, despite the use of high quality filters. This is due to such factors as ringing, blurring, aliasing, and anisotropic effects which cannot all be simultaneously minimized (see, for example, [Mitchell and Netravali 88]). More importantly, discontinuities become increasingly smeared as one increases the size, since the convolution assumes a band-limited signal, i.e. an image with no edges. This has practical implications when texture mapping is used to define the color of surfaces in 3D: since a texture map can be enlarged arbitrarily, a brick texture, for example, will become diffuse instead of exhibiting distinctly separate bricks. Now consider applying affine transformations to images represented by quadtrees, a spatial structure, developed within the context of a finite discrete space, for reducing verbosity and inducing structure on an image. The algorithm for constructing the new quadtree of the transformed image seems relatively complicated when compared to the corresponding algorithms for continuous space representations: it must resample each transformed leaf node and construct an entirely new tree. In contrast, boundary representations, simplical decompositions, or binary space partitioning trees only require transforming points and/or

Motion image data compression coding apparatus and image data compression coding method

Abstract: A motion image data compression coding apparatus and an image data compression coding method capable of smoothing compressed data among frames are disclosed. A data amount of compressed data is obtained by a hybrid coding of a combination of an orthogonal transform such as a discrete cosine transform, a quantization and a variable length coding of motion image data of one frame. A quantization step size is expressed by a product of a scaling factor f and quantization matrix factors q. The scaling factor f is determined from a code amount produced up to the preceding frame, a target code amount and an AC level of the transform factors of the present frame. Prior to the quantization and the variable length coding, a code amount actually resulted by the same coding is detected, and by considering the actual code amount, the scaling factor f for the last quantization is corrected.

Sequential pipelined processing for the compression and decompression of image data

Abstract: A sequential process-pipeline has a first processing stage (30) coupled to a CODEC (24) through a plurality of buffers, including an image data input buffer (28), an image data output buffer (26), and an address buffer (34). The image data input buffer stores, for each block of image data, control information for controlling the processing of an associated block of image data. The address buffer stores addresses, each of which identifies an initial address of a block of addresses within an image memory (22). A local controller (18) is responsive to the writing of an address into the address buffer to read the control information for a block to be processed, and to initiate the operation of the CODEC, in accordance with the read-out information, to execute a Discrete Cosine Transformation Process and a Discrete Cosine Transformation Quantization Process.

A forward-mapping realization of the inverse discrete cosine transform

Abstract: The paper presents a new realization of the inverse discrete cosine transform (IDCT). It exploits both the decorrelation properties of the discrete cosine transform (DCT) and the quantization process that is frequently applied to the DCT's resultant coefficients. This formulation has several advantages over previous approaches, including the elimination of multiplies from the central loop of the algorithm and its adaptability to incremental evaluation. The technique provides a significant reduction in computational requirements of the IDCT, enabling a software-based implementation to perform at rates which were previously achievable only through dedicated hardware. >

Pixel quantization with adaptive error diffusion

Abstract: A method of image conversion takes an original print ready image at a first resolution scaling and orientation, and simulates printing that image by creating a representation of a page at the particular resolution, scaling and orientation. The image is then periodically sampled through the page with an aperture that corresponds to the desired output. Because the resolution, scaling and/or orientation of the "print" and "scan" are distinct, the aperture "sees" areas which may correspond to more than a single pixel on the original image, and thereby may derive a signal that is gray, i.e., the aperture may see an area that is neither completely black or white, and the image data derived will be considered gray. The gray image data, which may be definable at several bits per pixel, is then made print-ready by reducing the number of bits defining each pixel to a valid output state. The reduction step is accomplished through an adaptive error diffusion method, in which thresholding error is directed only to members of a set of error receiving pixels already having a valid output state. When all the error receiving pixels have a valid output state, error is directed to those pixels in accordance with a standard error diffusion method.

ECG data compression using the discrete cosine transform (DCT)

Abstract: Orthogonal transforms provide alternate signal representations that can be useful for electrocardiogram (ECG) data compression. The goal is to select as small a subset of the transform coefficients as possible which contain the most information about the signal, without introducing objectionable error after reconstruction. With a sampling rate of 1 kHz, more than 99% of the power in the DCT is contained within the first 20% of the coefficients. Despite this result a 5:1 compression ratio cannot be obtained by merely substituting zero for the remaining 80%. The coefficients after the first 20%, although of relatively small magnitude, preserve the DC integrity of the signal. Approximating these components as zero leads to introduction of spurious sinusoidal terms in the reconstructed signal. A quantization technique to better approximate the higher coefficients has been used to obtain an accurate representation of the signal. The tradeoffs between accuracy, speed, and compression ratio are discussed. >

Relevance of human vision to JPEG-DCT compression

Abstract: This paper asks how the vision community can contribute to the goal of achieving perceptually lossless image fidelity with maximum compression. In order to maintain a sharp focus the discussion is restricted to the JPEG-DCT image compression standard. The numerous problems that confront vision researchers entering the field of image compression are discussed. Special attention is paid to the connection between the contrast sensitivity function and the JPEG quantization matrix.

Improved video signal quantization for an MPEG like coding environment

Abstract: A quantization parameter for use in encoding a region of an image is developed from a) a categorization of the region into one of a predetermined plurality of perceptual noise sensitivity (PNS) classes, b) a level of psycho-visual quality that can be achieved for the encoded version of the image, the level being selected from among a plurality of predetermined levels, and c) a prestored empirically derived model of the relationship between the PNS classes, the psycho-visual quality levels and the values of the quantization parameter. PNS indicates the amount of noise that would be tolerable to a viewer of the region, i.e., the perceptual sensitivity of the region to noise. Some characteristics on which PNS classes may be based are : spatial activity, speed of motion, brightness of the region, importance of the region in a particular context, the presence of edges within the region and the texture of the region, e.g., from "flat" to "highly textured". PNS classes that include combinations of the characteristics of a region of the image may also be defined. The PNS classes employed are selected by the implementor and may be determined empirically. The psycho-visual quality of an encoded image is the quality, as perceived by a viewer, of the version of the image that is reconstructed from the encoded image. It is determined from the complexity of the image and the bit-rate available to encode the image.

Method and apparatus for encoding selected images at lower resolution

Abstract: A method and apparatus for encoding a sequence of digital motion video images at more than one resolution. In a first embodiment, it is determined whether an image selected from the sequence is part of either a dissolve, a fade, a fast motion region or a complex motion region. If the selected image is part of either a dissolve, a fade, a fast motion region or a complex motion region, then the selected image is encoded at a reduced resolution level. In a further embodiment, a selected image is provided for encoding. A determination is then made whether a parameter derived from an estimate of the available decoding time is above a predetermined threshold. If the parameter is above the predetermined threshold, then the selected image is encoded at a reduced resolution. In a still further embodiment, a selected image from a sub-sequence of images is provided for encoding. A determination is then made whether the quantization step size associated with the image is greater than a predetermined threshold. If the quantization step size is greater than the predetermined threshold, then the image is encoded at a reduced resolution. The image is partially encoded if it is within the first N minus one images provided from the sub-sequence, otherwise the image is fully encoded.

Orthogonal transform encoder using DC component to control quantization step size

Abstract: According to orthogonal transformation coefficients obtained through orthogonal transformation, the degree of influence on visual sensation is detected Depending on the degree of influence on visual sensation, a quantization step size is controlled so as to assign a greater amount of codes to each block of which image quality deterioration is conspicuous and a smaller amount of codes to each block of which image quality deterioration is less conspicuous

Image processing apparatus and terminal apparatus

Abstract: The present invention is directed to a terminal apparatus in which the in-frame compression factor of an image obtained by a camera is increased to restrict frame thinning when the camera is moved. A control circuit 60 performs control of a movable table 12. When a TV camera 10 is moved, the quantization table used in a quantization circuit 26 is changed over, whereby a higher compression factor of the coding conducted by a DCT circuit 24 and the quantization circuit 26 is achieved. Thus, a predetermined compression factor can be achieved without performing frame thinning.

Picture encoding and/or decoding method and apparatus

Abstract: A picture encoding and/or decoding system adaptively changes encoding manner in discrete cosine transformation or predictive coding for improving a picture quality of transmission picture. A variable length coding method is changed in accordance with the change between the discrete cosine transformation and predictive coding. When discrete cosine transforming, a combination of a zero run length and a pixel value is effected two dimensional variable length coding. When predictive coding, a combination of a zero run length and a difference value between pixel values is effected two dimensional variable length coding. When predictive coding, a predictive value of a block and a quantization width are transmitted.

Programmable vision processor/controller for flexible implementation of current and future image compression standards

Abstract: The vision processor (VP) and vision controller (VC), two integrated products dedicated to video compression, are discussed. The chips implement the P*64, JPEG, and MPEG image compression standards. The VP forms the heart of the image compression system. It performs discrete cosine transform (DCT), quantization, and motion estimation, as well as inverse DCT, and inverse quantization. The highly parallel and microcode-based processor performs all of the JPEG, MPEG, and P*64 algorithms. The VC smart microcontroller controls the compression process and provides the interface to the host system. It captures pixels from a video source, performs video preprocessing, supervises pixel compression by the VP, performs Huffman encoding, and passes the compressed data to the host over a buffered interface. It takes compressed data from the host, performs coder decoding, supervises decompression via the VP, performs postprocessing, and generates digital pixel output for a video destination such as a monitor. >

A neural network based image compression system

Abstract: It is proposed that vector quantization be implemented for image compression based on neural networks. Separate codebooks for edge and background blocks are designed using Kohonen (1984) self-organizing feature maps to preserve edge integrity and improve the efficiency of codebook design. A system architecture is proposed, and satisfactory performance is achieved. >

Orthogonal transformation encoder

Abstract: In a data compression encoder for a video signal the degree of influence on visual sensation is detected by obtaining orthogonal transformation coefficients by carrying out an orthogonal transformation in a circuit (2). Depending on the degree of influence on the visual sensation, the quantization step size is controlled by a control circuit (4) so as to assign a greater amount of codes to each block in which the image quality deterioration would be conspicuous and a smaller amount of codes to each block in which the image quality deterioration would be less conspicuous.

Imaging system with multilevel dithering using two memories

Abstract: Disclosed is an image processing system which relies upon quantization and dithering techniques to enable an output device, which has a given number of output levels, to accurately reproduce a image which is generated by an input device, which has a greater or equal number of input levels. Generally, neither the number of input nor output levels need to be a power of two. The present invention is implemented in a number of different embodiments. These embodiments generally rely upon an image processor which, depending on the particular implementation, includes memory devices and an adder, a comparator, or a bit shifter. Additional embodiments use an image adjustment system to refine the raw input levels of the input device, in order to create an improved output image. Also, the particular embodiments of the image processors can be used in connection with imaging systems having bi-tonal, monochromatic, or color input and output devices.

DCT-based still image compression ICs with bit-rate control

Abstract: The authors discuss compression and coding ICs for still images based on the DCT (discrete cosine transform) using a new algorithm for bit-rate control. The compression and coding method used in these ICs conforms to the JPEG (Joint Photographic Expert Group) standard. These ICs have been developed for a digital still camera system using memory cards as the recording medium, and they have a bit-rate control function to guarantee the number of images recorded on a card. The functional specifications and composition of these ICs, as well as the structure of the encoder IC, and details of the algorithm used for bit-rate control are considered. >