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Image Compression Techniques Using Lossless Methods:A Review
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In recent years there has been an astronomical increase in the usage of computers for a variety of tasks. With the advent of digital cameras, one of the most common uses has been the storage, manipulation, and transfer of digital images. The files that comprise these images, however, can be quite large and can quickly take up precious memory space on the computer’s hard drive. In multimedia application, most of the images are in colour. And colour images contain lot of data redundancy and require a large amount of storage space. Image compression algorithms offer the means to minimize storage cost and to increase transmission speed. Compressing an image is significantly different than compressing raw binary data. Of course, general purpose compression programs can be used to compress images, but the result is less than optimal. This is because images have certain statistical properties which can be exploited by encoders specifically designed for them. Also, some of the finer details in the image are sacrificed for the sake of saving a little more bandwidth or storage space. This also means that lossy compression techniques cannot be used. Hence there is a need for efficient lossless schemes for medical image data. Lossless data compression is used in many applications. For example, it is used in the ZIP file format and in the UNIX tool gzip. It is also often used as a component within lossy data compression technologies (e.g. lossless mid/side joint stereo pre-processing by the LAME MP3 encoder and other lossy audio encoders). Several lossless compression schemes have been proposed. This paper provides a comparison and brief description about the various lossless compression schemes.
Keywords
SPIHT, DICOM, Wavelets, JPEG, MPM Code, Multi-Scale Segmentation.
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