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 Dec 2008TL;DR: The layered multicast encryption proposal allows a sender to multicast hierarchical encrypted JPEG 2000 code streams such that only designated groups of users can de-crypt the code streams.
Abstract: This paper proposes the hierarchical encryption of Motion JPEG 2000 code streams for layered multicast transmission. JPEG 2000 generates hierarchical code streams and offers flexible scalability in characteristics such as resolution and SNR. The layered multicast encryption proposal allows a sender to multicast hierarchical encrypted JPEG 2000 code streams such that only designated groups of users can de-crypt the code streams. The encrypted bitstreams produced by the proposed method comply fully with JPEG 2000.
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01 Nov 2011TL;DR: A novel watermarking algorithm in digital images to ensure the imperceptible characteristics of the watermarks, reducing the effects on images quality while maintaining recoverability is proposed.
Abstract: This paper proposes a novel watermarking algorithm in digital images to ensure the imperceptible characteristics of the watermarks, reducing the effects on images quality while maintaining recoverability. The proposed method is performed by embedding watermarks in the DCT domain. DCT coefficients, which are selected to be embedded, or not, are based on an evaluation of watermark robustness during the quantization phase of the JPEG Baseline method. Results of the algorithm have been evaluated using Matlab.
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01 Dec 2004TL;DR: This paper presents a block based lossless compression approach for gray scale images by selecting a scanning that produces the best result on each block, and a newly proposed adaptive linear prediction is performed.
Abstract: This paper presents a block based lossless compression approach for gray scale images. Multiple scanning methods are applied to each block, and a newly proposed adaptive linear prediction is performed. There are different prediction residuals obtained corresponding to different context based on multiple scanning. We choose the best residual for coding. That is, rather than relying on any single scanning, our approach is to select a scanning produces the best result on each block. The prediction coefficients are updated during the scanning to optimize the coding accuracy. Experiment results show that our method outperformed JPEG-LS 4-5% in compression efficiency.
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TL;DR: The basic architecture of the JPEG2000 is implemented using MATLAB and can be used for both gray-scale and colour images, which is being designed to address the requirements of a diversity of applications, e.g. internet, colour facsimile, printing, scanning, digital photography, remote sensing, mobile applications, medical imagery, digital library and E-commerce.
Abstract: In the last few years technology advancement of digital processors and digital storage devices have resulted in dramatic reduction in the size and cost of digital memory and digital processing logic. The manipulation and analysis of digital pictorial information is referred to as digital image processing. Image data compression comes under the category of digital image processing. Image compression is the method of effectively coding digital images to reduce the number of bits required in representing an image. The purpose of doing so is to reduce the storage and transmission costs while maintaining good quality. There are two methods of compression, Lossy compression and Lossless compression. With the increasing use of multimedia technologies, Image compression requires higher performance as well as new features. To address this, need in the specific area of still image encoding, a new standard is used, the JPEG2000. It is interesting to note that JPEG2000 is being designed to address the requirements of a diversity of applications, e.g. internet, colour facsimile, printing, scanning, digital photography, remote sensing, mobile applications, medical imagery, digital library and E-commerce. We have implemented the basic architecture of the JPEG2000 using MATLAB. It can be used for both gray-scale and colour images.