Enhancement of Compression Ratio and Image Quality using ISPIHT with MFHWT

Abstract

This paper presents a new approach for compression of medical images with MFHWT (Modified Fast Haar Wavelet Transform) and SPIHT (Set Partitioning In Hierarchical Trees). It provide high compression ratio with high picture quality. The Modified Fast Haar Wavelet Transform is used to decompose the image at different frequency levels. It has high multi-resolution characteristics. The CR (compression ratio) of proposed method is better than existing method (SPIHT). Medical images have a number of regions where intensity is changing slowly or even have a constant value. Such regions are compressed with higher compression ratio. In medical applications image distortion is not acceptable. So the quality of the images is also improved in proposed method in terms of PSNR (Peak Signal to Noise Ratio).

Representing a image using a Haar-Wavelet Transformation for human parts detection

“…The Compression ratio is defined as the ratio of an original image and compressed image [19]. Compression Ratio = Original Image / Compressed Image.…”

Medical Image Analysis and Processing Using a Dual Transform

“…Haar wavelet transform has been used as an earliest example for orthonormal wavelet transform with compact support. The haar transform (HT) is one of the simplest and basic transformations from a space domain are a local frequency domain and it reduces the calculation work [27]. HT decomposes the linear approximated image as approximation components and detail components.…”