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Enhanced lossy techniques for compressing background region of medical images using roi-based encoding.
| Content Provider | CiteSeerX |
|---|---|
| Abstract | Abstract-Image compression is an important task in medical imaging system and consists of mechanisms that reduce storage requirements while maintaining image quality. Medical image compression can be performed in a lossless or lossy fashion and a method that combines both is the Region of Interest (ROI) techniques. ROI techniques separate relevant and irrelevant details of an image and apply lossy technique to irrelevant part and lossless technique to relevant part. This paper proposes an enhanced active contour based ROI algorithm to separate the image as background and foreground. The foreground is compressed using a lossless JPEG algorithm and the background is compressed using an enhanced lossy JPEG algorithm that uses wavelet neural network followed by a post processing algorithm. Experimental results in terms of Compression Rate, Peak Signal to Noise Ratio and speed of compression show that the proposed scheme is an improved version when compared with the traditional algorithm. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Compressing Background Region Enhanced Lossy Technique Medical Image Using Roi-based Encoding Improved Version Wavelet Neural Network Lossy Fashion Lossless Jpeg Algorithm Irrelevant Detail Lossy Technique Medical Image Compression Medical Imaging System Roi Technique Image Quality Lossless Technique Important Task Compression Rate Abstract-image Compression Noise Ratio Roi Algorithm Storage Requirement Enhanced Active Contour Compression Show Traditional Algorithm Enhanced Lossy Jpeg Algorithm Peak Signal Post Processing Algorithm Experimental Result |
| Content Type | Text |
| Resource Type | Article |
