Showing papers on "JPEG 2000 published in 1997"

Joint thresholding and quantizer selection for transform image coding: entropy-constrained analysis and applications to baseline JPEG

Abstract: Striving to maximize baseline (Joint Photographers Expert Group-JPEG) image quality without compromising compatibility of current JPEG decoders, we develop an image-adaptive JPEG encoding algorithm that jointly optimizes quantizer selection, coefficient "thresholding", and Huffman coding within a rate-distortion (R-D) framework. Practically speaking, our algorithm unifies two previous approaches to image-adaptive JPEG encoding: R-D optimized quantizer selection and R-D optimal thresholding. Conceptually speaking, our algorithm is a logical consequence of entropy-constrained vector quantization (ECVQ) design principles in the severely constrained instance of JPEG-compatible encoding. We explore both viewpoints: the practical, to concretely derive our algorithm, and the conceptual, to justify the claim that our algorithm approaches the best performance that a JPEG encoder can achieve. This performance includes significant objective peak signal-to-noise ratio (PSNR) improvement over previous work and at high rates gives results comparable to state-of-the-art image coders. For example, coding the Lena image at 1.0 b/pixel, our JPEG encoder achieves a PSNR performance of 39.6 dB that slightly exceeds the quoted PSNR results of Shapiro's wavelet-based zero-tree coder. Using a visually based distortion metric, we can achieve noticeable subjective improvement as well. Furthermore, our algorithm may be applied to other systems that use run-length encoding, including intraframe MPEG and subband or wavelet coding.

Wavelet transforms in a JPEG-like image coder

Abstract: The discrete wavelet transform (DWT) is incorporated into the JPEG baseline system for image coding. The discrete cosine transform (DCT) is replaced by an association of two-channel filter banks connected hierarchically. The JPEG block-scanning and quantization schemes are adopted while we use JPEG's entropy coder. The changes in scanning can be incorporated into the transform block in such a way that the only part that needs to be changed in a JPEG framework is to replace the DCT by the DWT. Objective results and reconstructed images are presented demonstrating that the proposed coder outperforms JPEG and approaches the performance of more sophisticated and complex wavelet coders. However, it does not require full-image buffering nor imposes a large complexity increase.

Method, apparatus and computer program product for querying by image colors using JPEG image format

Abstract: A method, apparatus and computer program product are provided for querying by image colors using a JPEG format for images from the internet. First an image color is selected. A DCT coefficient is acquired from a JPEG image. The acquired DCT coefficient is compared with the selected image color. A match within the JPEG image is identified responsive to the acquired DCT coefficient being near the selected image color. An average color can be used for querying JPEG formatted images from the internet.

A JPEG codec adaptive to region importance

Abstract: This paper presents a novel standard baseline JPEG compatible still image compression method that allows to flexibly control the decompression quality of regions in image. Therefore, it allows both higher quality of important parts and lower bitrate as a whole, and it reflects the sense of human beings. We use fuzzy technique to determine important regions in the same manner as human beings do, allocate higher bitrate to important regions while lower to the rest parts of image. The paper introduces the important region determination, description, arbitrarily shaped region filling, importance adaptive image compression, decompression, and finally gives experimental results. Keywords— Adaptive codec, region importance, Human Visual System, JPEG, fuzzy reasoning.

Deblocking of JPEG-compressed images using wavelets

Abstract: This paper introduces a new approach to deblocking of JPEG compressed images using over-complete wavelet representations. By exploiting cross-scale correlations among wavelet coefficients, edge information in the JPEG compressed images is extracted and protected, while blocky noise in the smooth background regions is smoothed out in the wavelet domain. Compared with the iterative methods reported in the literature, our simple wavelet-based method has much lower computational complexity, yet it is capable of achieving the same PSNR improvement as the best iterative method, and giving visually very pleasing images as well.

The New Extended JPEGg Coder With Variable Quantizer Using Block Wavelet Transform

Abstract: This paper describe the new extended JPEG coder with variable quantizer using the block wavelet transform which has more flexibility in representing the image dye to a pyramid-like multiresolution decomposition. We replace the discrete cosine transform (DCT) module by block-wise discrete wavelet transform (BDWT) module while keeping all the building blocks of the JPEG extension coder. In addition, we generate the variable quantization matrix (Q-matrix) based on the human visual system (HVS) and utilize the activity of the each block to control the bit and image quality. The simulation results show that the proposed scheme has substantially better performance than the JPEG extensions.

Method for speeding up JPEG quantization operations in image compression

Abstract: A method for speeding up JPEG quantization operations in image compression for discrete cosine transform encoding operations in JPEG image compression. The quantization calculations are performed to obtain descriptors for Huffman encoding. The quantization calculations utilize a modified quantization table which is derived from an original quantization table by inversing each element of the original quantization table and then mutiplying 2 n and then rounding off. The matrix composed by discrete cosine transform coefficients multiplies the modified quantization table to derive a new matrix. Then, each element of the new matrix is right shifted n bits to derive quantized discrete cosine transform coefficients. Then, Huffman encoding is performed to accomplish discrete cosine transform encoding.

Check image compression: a comparison of JPEG, wavelet and layered coding methods

Abstract: An emerging trend in the banking industry is to digitize checks for storage and transmission. An immediate requirement for efficient storage and transmission is check image compression. General purpose compression algorithms such as JPEG and wavelet-based methods produce annoying ringing and blocking artifacts at high compression ratios. A layered approach to check image compression is proposed, based on which a check image is represented in several layers. The first layer describes the foreground map; the second layer specifies the gray levels of foreground pixels; the third layer is a lossy representation of the background image; and the fourth layer describes the error between the original and the reconstructed image based on the first three layers. The layered coding approach produces images of better quality than traditional JPEG and wavelet coding methods, especially in the foreground, i.e., the text and graphics. In addition, this approach allows progressive retrieval or transmission of different image layers.

A single chip motion JPEG codec LSI

Abstract: We have developed a single chip motion JPEG codec LSI that can compress and decompress VGA-size (640/spl times/480) JPEG images at the rate of 30 frames per second simply by connecting a single external buffer memory chip. The LSI uses compression ratio control to store a fixed number of images when there is limited memory capacity, and it compresses data stored in the frame buffer so that it can process signals at high speed without using high-speed image memory. The JPEG codec core is small (40,000 gates) and power consumption is low (220 mW) for broader application in image processing in consumer markets.