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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.


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Patent
08 Sep 2000
TL;DR: In this paper, the image data of 12 bits per pixel obtained by a CCD is separated into the high order side bit data of the high-order 8 bits of high correlation and the low-order side-bit data of low correlation.
Abstract: PROBLEM TO BE SOLVED: To compress and store image data obtained by high definition by high compressibility and to reproduce the stored image data at a high speed as images of a small data amount. SOLUTION: The image data of 12 bits per pixel obtained by a CCD 1 are separated into the high order side bit data of the high order 8 bits of high correlation and the low order side bit data of low correlation. JPEG lossless encoding is executed to the high order side bit data and a bit shift operation/ packing processing to two pixels is executed to the low order bit data. The processed high order side bit data and low order side bit data and position information for individually managing them are stored in a storage medium 2. Just by decoding the high order side bit data of the high correlation, the coarse images of the small data amount are reproduced at a high speed.

4 citations

Proceedings Article
03 Oct 2012
TL;DR: A comparison between JPEG and JPEG2000 –wavelet- based image compression based on the output from different images is attempted and the PSNR values are compared for different images.
Abstract: The paper attempts a comparison between JPEG and JPEG2000 –wavelet- based image compression based on the output from different images. Also the PSNR values are compared for different images. The paper also reviews the recent advancements in this area after the introduction of JPEG2000 so as to bring out the further research prospects in the field of image compression. General Terms Image compression, Huffman coding, low bit rate transmission, JPEG, JPEG 2000, wavelet, PSNR Keywords JPEG, JPEG2000, image compression, wavelet, DCT, 1. INTRODUCTION Image compression is an established and well researched segment which has been undergoing significant advances over the period of time. Keeping in view the on-going advancements taking place in this field, the paper focuses on the recent advances in this field starting with the two latest image compression standards, such as JPEG and JPEG2000 the distinguishing feature of JPEG2000 being wavelet based image compression. After comparing the theoretical differences vis-a-vis the experimental results of these key standards, the paper also details some of the recent studies in the field of wavelet based image compression.

4 citations

Proceedings ArticleDOI
07 May 2006
TL;DR: In this paper, a new architecture for lossless compression of microarray images is offered, using a dedicated hardware for separation of foreground pixels from the background ones and using pipeline architecture.
Abstract: Microarray technology is a recent and powerful tool for concurrent monitoring of large number of genes expressions. Every microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence, real-time processing of these images and transmission of them necessitates efficient and custom-made lossless compression schemes. In this paper, we offer a new architecture for lossless compression of microarray images. In this architecture, we have used a dedicated hardware for separation of foreground pixels from the background ones. By separating these pixels and using pipeline architecture, a higher lossless compression ratio has been achieved as compared to other existing methods.

4 citations

Journal Article
TL;DR: An universal steganalytic scheme using blocks of the JPEG file binary output stream and compute higher order statistics over their Hamming weights and combined them with a Kullbak-Leibler distance between the probability density function of these weights and a benchmark one.
Abstract: We present in this paper a new approach for universal JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. We design an universal steganalytic scheme using blocks of the JPEG file binary output stream. We compute higher order statistics over their Hamming weights and combined them with a Kullbak-Leibler distance between the probability density function of these weights and a benchmark one. We evaluate the universality of our detector through its capacity to efficiently detect the use of a new algorithm not used during the training step. To that goal, we examinate training sets produced by Outguess, F5 and JPhide-and-Seek. The experimental results we obtained show that our scheme is able to detect the use of new algorithms with high detection rate (≃ 90%) even with very low embedding rates (< 10-5).

4 citations

Proceedings ArticleDOI
05 Mar 2015
TL;DR: Face detection suggested in this paper detects the face with the detection of skin color and natural dimensional ratio of height to width of normal human face.
Abstract: Region of Interest based compression is an efficient method of compression for images with a particular part to be most significant. It is always a better choice to compress the ROI with lossless compression while the rest of image with lossy compression technique. This paper deals with the compression of color images with the face of the person (ID cards, voter ID). This paper proposes lossless compression for face (ROI) and near lossless compression for the rest of the image. Image other than ROI may contain information that is useful, that is why it is appropriate to use near lossless compression for the rest of the image. Face detection suggested in this paper detects the face with the detection of skin color and natural dimensional ratio of height to width of normal human face. In this method of compression, PSNR obtained is remarkable and compression ratio can be increased by increasing the base value which is in power of two. In this method of compression, face will be compressed completely lossless by using Huffman coding and Snake difference scanning is used for achieving a good compression ratio. Proposed algorithm provides quality PSNR with reasonable CR with lossless compression of ROI.

4 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202321
202240
20215
20202
20198
201815