Image Compression Techniques for Medical Applications

Abstract

Image compression is one of the best method which can reduce the storage space of images, videos and helpful to increase storage space and transmission process's performance. With pace of time medical imaging it become one of the most crucial sub-fields in the world of science and technology and Medical images are used to diagnose a variety of illness can't make any compromise in the quality. Developing some new algorithm and with the help of various de-noising method plays a major role in image processing. In this paper, Discrete wavelet transform(DWT) image decomposed into eight subbands and after that bilateral filter and thresholding methods are used. In this research work using second level DWT is used and approximation coefficient are obtained from DWT filtered using bilateral filter and the detail coefficients are subjected to Wavelet Thresholding. Image is reconstructed by the inverse wavelet transform(IDWT) of the resultant coefficients and the filtered using bilateral filter. Use of IDWT twice as using second level DWT in process and its main motive to achieve better result as compared to base paper. Various types of images Can use as datasets for quantitative validation. The Peak Signal to Noise Ratio (PSNR), Mean square error (MSE) parameters are calculated with respect to bilateral parameters

Adaptive Polynomial Fitting for Image Compression Based on Variance of Block Pixels

“…They are widely used in most applications when the quality of images is not the mean issue. These techniques include: transformation coding (such as discrete Fourier transform (DFT), discrete cosine transform (DCT), and discrete wavelet transform (DWT)) [7][8][9], vector quantization, fractal coding, block truncation coding (BTC), and subband coding [10].…”