We analyzed the performance of several lossless image compression algorithms, namely Lossless JPEG, JPEGLS, JPEG2000, PNG, and CALIC on a large set of medical retinal images organized into groups according to capturing conditions and retinal region. Overall we found JPEG-LS to be the best performing algorithm when we consider both compression speed and compression ratio. Although we observed so...

This paper proposes lossless image compressors that are simpler than existing ones and yet still work well. The compressors process images in raster-scan order, and to code a pixel first estimate that pixel’s value by using a linear function of already-coded pixels. Next the compressors estimate the uncertainty in the first estimate by using a nonlinear function of already-coded pixels. Finally...

The demand to preserve raw image data for further processing has been increased with the hasty growth of digital technology. In medical industry the images are generally in the form of sequences which are much correlated. These images are very important and hence lossless compression Technique is required to reduce the number of bits to store these image sequences and take less time to transmit...

Here, the concept of compression theory and lossless image compression methods are studied. In order to preserve the value of diagnostic medical images, it is necessary to provide lossless image compression. Apart from practical reasons, there are often legal restrictions on the lossless medical image compression. Lossless data compression has been suggested for many space science exploration m...

Most single-frame single-band medical images, like CR, CT, and MR, are of a high nominal bit depth, which usually varies from 12 to 16 bits per pixel. The actual number of pixels' intensity levels found in those images may be smaller, than implied by the nominal bit depth, by an order of magnitude or even more. Furthermore, levels are distributed throughout almost all the entire nominal intensi...

Dictionary-based encoding methods are popular forms of data compression. These methods were initially implemented to reduce the one-dimensional correlation in data, since they are designed to compress text. Therefore, they do not take advantage of the fact that adjacent pixels in images are correlated in two dimensions. Previous attempts have been made to adapt dictionary-based compression sche...

To display high bit resolution images on low bit resolution displays, bit resolution needs to be reduced. Towards achieving a reduced bit rates and high compression gain, an enhanced method for compression of various color images are presented, which is based on hierarchical prediction and adaptive coding. An RGB image is first transformed to YCbCr by a reversible color transform and a various ...

State-of-the-art lossless image compression schemes, such as JPEG-LS and CALIC, have been proposed in the context-adaptive predictive coding framework. These schemes involve a prediction step followed by context-adaptive entropy coding of the residuals. However, the models for context determination proposed in the literature, have been designed using ad-hoc techniques. In this paper, we take an...

Still image coding occasionally uses linear predictive coding together with multi-resolution decompositions, as may be found in several papers. Those related approaches do not take into account all the information available at the decoder in the prediction stage. In this paper, we introduce an adapted generalized lifting scheme in which the predictor is built upon two filters, leading to taking...