: Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes impercep...

This paper presents a lossy image compression scheme that employs a generalized rank-ordered prediction filter for pyramidal image coding. The proposed prediction method renders significantly reduced variance of the quantizer input. Consequently, the quality of the decompressed image is much enhanced due to the greatly reduced quantization distortion. Both analytical and simulation results show...

Data compression refers to the process of representation data using fewer number bits. can be lossless or lossy. There are many schemes developed and used perform either lossy compression. Lossless allows original conveniently reconstructed from compressed while allow only an approximate constructed. The type classified as image data, textual audio even video content. Various researches being c...

The bandwidth reduction or storage lowering in digital image transmission confers to the image compression a key role. In this paper, we propose a new approach for lossy image compression: the source image is vector quantized by applying Self-Organizing Map (SOM) with several dictionaries. Each dictionary is originally designed based on the feature vectors resulted after applying the Walsh-Hada...

In the paper is presented one new approach for efficient decorrelation of multispectral images, based on hierarchical adaptive Principal Component Analysis. The research is aimed at the efficient compression of multispectral images (MS), whose resolution and band number in some application areas are extremely high. Together with this, also grows up the needed volume of the corresponding image d...