An Intelligent New Age Method of Image Compression and Enhancement with Denoising for Bio-Medical Application
Keywords:
SPIHT, Histogram Equalization, DWT, contrast enhancement, Impulse noise, Improved Switching Median FilterAbstract
Image compression is the reduction or elimination of redundancy in data representation in order to achieve reduction in storage and communication costs. In this paper, we are presenting the wavelet using SPIHT algorithm to compress the gray color images. This finds the coefficients of uncompressed image and minimize the number of bits to represent the image. The Huffman encoder is also designed in which the JPEG standardized table values are used for further compression. The compression of an image is followed by enhancement techniques to improve the contrast of an image. An enhancement algorithm is one that yields a better quality image for the purpose of some particular application which can be done by either suppressing the noise or increasing the image contrast Enhancement of image, One of the conventional methods adopted is the Histogram Equalization (HE) technique. The main limitation of this technique causes unpleasant visual artifacts, such as over enhancement, level saturation and raised noise level. Histogram Equalization with Improved Switching Median Filtering technique (WTHEISMF) which eliminates the impulse noise and preserves the edges of an image. This paper presents the parameters comparison and simulation results of HE, WTHE and WTHEISMF with Absolute Mean Brightness Error (AMBE), Measure of Enhancement (EME), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE).
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