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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14 Sep 2005
TL;DR: This work proposes a method for improvement the tolerance on the geometrical operations as attacks to the watermarked JPEG image.
Abstract: A method of embedding binary data into JPEG bitstreams has been reported in [1]. However, attacks as geometrical operations to the watermarked JPEG image data have not been analyze. In this work, we propose a method for improvement the tolerance on the geometrical operations as attacks to the watermarked JPEG image.
Patent•
22 Mar 2006
TL;DR: In this paper, a process for improved, lossless data transformation with options for adaptive compression (150), multidimensional prediction (170), multi-symbol decoding (670), was presented.
Abstract: A process for improved, lossless data transformation with options for adaptive compression (150), multidimensional prediction (170), multi-symbol decoding (670).
01 Jan 2013
TL;DR: The lossless compression method is extremely efficient when used for coding of images of biomedical signals of any kind and has relatively low computational complexity, which is a reason to propose its use in telemedicine and in medical support appliances.
Abstract: In this work are presented some new approaches for efficient archiving of visual medical information of various kinds. The main attention is aimed at the archiving of scanned paper documents. For this, new algorithms for image preprocessing and object segmentation are presented. The preprocessing is based on adaptive filtration, used to reduce the noises in the image background (corresponding to the image of the paper), retaining the main information (graphics, texts, etc.) untouched. The lossless compression, whose algorithm is given in detail, is based on new method for adaptive run-length coding, which comprises image histogram analysis and data coding. Significant advantage of the method is that it never allows enlargement of the coded files. The work comprises also experimental results, obtained using the software implementation of the algorithm and comparison with the well-known standards JPEG and JPEG 2000. The method is extremely efficient when used for coding of images of biomedical signals of any kind and has relatively low computational complexity, which is a reason to propose its use in telemedicine and in medical support appliances. Same approach is suitable for use in wide variety of applications (for example, telemedicine, etc.), which is proved by the experimental results included.
30 Apr 1996
TL;DR: The article reviews and summarizes the results of a Norden study to evaluate real-time JPEG and wavelet compression of the RS-170 images taken from the display of the APG-76 high resolution SAR multimode radar system and transmitted to the ground.
Abstract: The article reviews and summarizes the results of a Norden study to evaluate real-time JPEG and wavelet compression of the RS-170 images taken from the display of the APG-76 high resolution SAR multimode radar system and transmitted to the ground. The significant advantages of this compression are twofold: the ability to retain large quantities of flight test images at better compression rates than that provided by the lossless GIF format; and the ability to transmit the images in near-real time from the ground station to a home base over standard telephone lines or even over a cellular phone. We have investigated several techniques, considered in the literature to be at or near the state of the art, for lossy compression of APG-76 radar images captured on the ground. We have achieved up to 15:1 in JPEG compression rates without significant picture degradation, if the images are first de-noised. If the pictures are not de-noised, then an 8:1 compression rate can be achieved with little degradation, but at 15:1, JPEG does degrade the images. Although in 1995 we could find no wavelet technique that bettered JPEG, we recently acquired a wavelet implementation that, at 15:1 compression, measured nearly 30 dB in peak signal to noise ratio (PSNR), and was 1.6 dB better than JPEG. This represents a long step towards the 3 dB PSNR improvement required to achieve 2:1 compression improvement over JPEG.
TL;DR: A memory- assisted hybrid compression technique is proposed that is motivated by using a combination of methods, lossy and lossless, to achieve better compression ratio.
Abstract: Image compression can be done in two ways namely lossy or lossless. Lossy methods are used for expected results like photographs where some negligible loss of data is tolerable. Rapid growth of medical science such as ehealth and telemedicine requires lossless Image compression. The correlation and redundancy which exists across different medical images are considered to achieve better compression ratio. . Better compression results in less storage and less overhead while transmission on the network. A memory- assisted hybrid compression technique is proposed. The approach is motivated by using a combination of methods, lossy and lossless. The original image is compressed using PCA algorithm and then using lossless coding methods. PCA is used to find the correlation among the similar medical images. PCA algorithm is used with only some principal components.