Topic
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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01 Jan 2009
TL;DR: Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.
Abstract: A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 8×8 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform (DCT) is applied to generate DCT coefficients: one DC coefficient and 63 AC coefficients in frequency coeffi- cients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.
TL;DR: The experimental results show that the Contourlet transform reduces the bit rates compared with prediction method, and has better convergence and finds the direct discrete-space construction to get flexible multiresolution, and better image compression.
Abstract: --The paper presents the lossless image compression based on prediction and contourlet transform methods in image processing. The lossless compression usually a less bandwidth or less memory and low compression ratio at the cost of image quality degradation. In the paper presents prediction and Contourlet transform methods are used. In prediction method, convert the color image to YVU and then apply the hierarchical scheme of upper, left, and lower pixels for the pixel prediction and arithmetic coding is added to the error signal corresponding to each context. In Contourlet transform has better convergence and finds the direct discrete-space construction to get flexible multiresolution, and better image compression. The experimental results show that the Contourlet transform reduces the bit rates compared with prediction method. Keywords--Lossless color image compression, hierarchical prediction, context adaptive arithmetic coding and Contourlet transform.
23 Apr 2014
TL;DR: A comparative study on the efficiency of predictors mostly used in the lossless image compression has been done for the infrared images with high bit-depth acquired for scientific purposes and experimental results have been presented as well.
Abstract: The requirements for the storage and transmission of image data are rapidly increasing due to rapid developments in technology. The storage and transmission of huge amount of the image data can be expensive. Researches on reducing the cost of storage and transmission and giving an opportunity to new applications keep still popularity. Many image compression schemes perform lossy compression. Lossy compression scheme meets the requirements for many applications. However, the needs for lossless image compression keep necessity for medical, scientific and professional applications. One of the crucial steps used in the lossless image compression is the prediction to remove spatial redundancy. In this paper, a comparative study on the efficiency of predictors mostly used in the lossless image compression has been done for the infrared images with high bit-depth acquired for scientific purposes and experimental results have been presented as well.
Patent•
18 Dec 2014TL;DR: In this paper, a JPEG image is preprocessed to enable parallel decoding by embedding restart (RST) markers within the JPEG data and embedding information in an application (APPn) marker.
Abstract: Devices, systems and methods are disclosed for preprocessing JPEG images to enable parallel decoding and for parallel decoding of JPEG images. A JPEG image may be preprocessed to enable parallel decoding by embedding restart (RST) markers within the JPEG data and embedding information in an application (APPn) marker, which may be included in a header associated with the JPEG data. Using the RST markers and information included in the APPn marker, a device may separate the JPEG data into sections and decode the sections in parallel using multiple cores to reduce a time between acquiring and rendering the JPEG image. The parallel outputs may be stored to identified locations in a buffer so that the finished outputs are sequentially stored as a complete decoded JPEG image.
09 Jul 2006
TL;DR: This paper advances an optical JPEG color image compression algorithm and discusses its performance, using statistical metrics such as mean square error and peak signal-to-noise ratio to quantify the difference between the original and reconstructed image quality.
Abstract: In this paper we advance an optical JPEG color image compression algorithm and discuss its performance. Statistical metrics such as mean square error (MSE) and peak signal-to-noise ratio (PSNR) are used. These quality criteria quantify the difference between the original and reconstructed image. The time required for compression/decompression using our optical method is one of the considered performance factors. Simulation results are presented to illustrate the effect of the compression ratio on the reconstructed image quality.