Lossless JPEG

About: Lossless JPEG is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 51110 citations. The topic is also known as: Lossless JPEG & .jls.

JPEG 2000 MQ-coder registry based error detection for lossy transmission channels

Abstract: In this paper we present a new method to produce low overhead redundant bits used to detect transmission errors of J2K streams on noisy communication channels. This method takes advantage of algorithms already existing on the JPEG 2000 standard and does not require any intrusive alterations on the coder. We will show that it is possible to improve standard JPEG 2000 error resilience in exchange for null resource footprint. Remark that this capability can be very important, for example in wireless communications that are mainly used by mobile devices with small processing capabilities.

Conditions for Effective Detection and Identification of Primary Quantization of Re-Quantized JPEG Images

Abstract: The choice of Quantization Table in a JPEG image has previously been shown to be an effective discriminator of digital image cameras by manufacturer and model series. When a photograph is recompressed for transmission or storage, however, the image undergoes a secondary stage of quantization. It is possible, however to identify primary quantization artifacts in the image coefficients, provided that certain image and quantization conditions are met. This paper explores the conditions under which primary quantization coefficients can be identified, and hence can be used image source identification. Forensic applications include matching a small range of potential source cameras to an image.

Lossless Image Compression by Block Matching on Practical Massively Parallel Architectures.

Abstract: Work-optimal O(log M log n) time implementations of lossless image compression by block matching are shown on the PRAM EREW, where n is the size of the image and M is the maximum size of the match, which can be implemented on practical architectures such as meshes of trees, pyramids and multigrids. The workoptimal implementations on pyramids and multigrids are possible under some realistic assumptions. Decompression on these architectures is also possible with the same parallel computational complexity.

Ga-based DCT quantization design for medical images

Abstract: The Joint Photographers Expert Group (JPEG) developed an image compression tool, which is one of the most widely used products for image compression. One of the factors that influence the performance of JPEG compression is the quantization table. Bit rate and the decoded quality are both determined by the quantization table simultaneously. Therefore, the designed quantization table has fatal influences to whole compression performance. The goal of this paper is to seek sets of better quantization parameters to raise the compression performance that means it can achieve lower bit while preserving higher decoded quality. In our study, we employed Genetic Algorithm (GA) to find better compression parameters for medical images. Our goal is to find quantization tables that contribute to better compression efficiency in terms of bit rate and decoded quality. Simulations were carried out for different kinds of medical images, such as sonogram, angiogram, X-ray, etc. Resulting experimental data demonstrate the GA-based seeking procedures can generate better performance than the JPEG does.