In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.
General TermsMultiresolution and polynomial approximation within high synthetic coding architecture for lossless image compression.
In this paper, an efficient image compression scheme is introduced, it is based on partitioning the image into blocks of variable sizes according to its locally changing image characteristics and then using the polynomial approximation to decompose image signal with less compressed information required compared to traditional predictive coding techniques, finally Huffman coding utilized to improve compression performance rate. The test results indicate that the suggested method can lead to promising performance due to simplicity and efficiency in terms of overcoming the limitations of predictive coding and fixed block size.
General TermsQuadtree partitioning of variable block sizes with polynomial approximation for lossy image compression.
JPEG is most popular image compression and encoding, this technique is widely used in many applications (images, videos and 3D animations). Meanwhile, researchers are very interested to develop this massive technique to compress images at higher compression ratios with keeping image quality as much as possible. For this reason in this paper we introduce a developed JPEG based on fast DCT and removed most of zeros and keeps their positions in a transformed block. Additionally, arithmetic coding applied rather than Huffman coding. The results showed up, the proposed developed JPEG algorithm has better image quality than traditional JPEG techniques.
Image compression is a serious issue in computer storage and transmission, that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information
Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the mathematical model and the residual.
In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless compression scheme of first stage that corresponding to second stage.
The tested results shown are promising in both two stages, that implicilty enhanced the performance of traditional polynomial model in terms of compression ratio , and preresving image quality.
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