Abstract
This paper consists of a lossy image compression algorithm dedicated to the medical images doing comparison of RGB and YCbCr color space. Several lossy/lossless transform coding techniques are used for medical image compression. Discrete Wavelet Transform (DWT) is one such widely used technique. After a preprocessing step (remove the mean and RGB to YCbCr transformation), the DWT is applied and followed by the bisection method including thresholding, the quantization, dequantization, the Inverse Discrete Wavelet Transform (IDWT), YCbCr to RGB transform of mean recovering. To obtain the best compression ratio (CR), the next step encoding algorithm is used for compressing the input medical image into three matrices and forward to DWT block a corresponding containing the maximum possible of run of zeros at its end. The last step decoding algorithm is used to decompress the image using IDWT that is applied to get three matrices of medical image.
Highlights
The basic objective of image compression is to reduce the size of image data for transmission or store in an efficient manner, while maintaining the suitable quality of reconstructed images [1,2,3]
The aim of this paper is to evaluate the performance of lossy medical image compression wavelet transforms followed by wavelet encoders experiments which were performed by using magnetic resonance images (MRI) as test images
The method is dedicated to lossy medical image compression Discrete Wavelet Transform (DWT) based and two phases of compression/decompression
Summary
The basic objective of image compression is to reduce the size of image data for transmission or store in an efficient manner, while maintaining the suitable quality of reconstructed images [1,2,3]. The easy and reliable digital transmission and storage of biomedical images would be a tremendous boon to the medical practices This can help in instant availability of earlier imaging studies when patients are re-admitted [4,5,6]. Both Medical and surgical teams indulging on patient care could have simultaneous access to imaging studies on monitors throughout the hospital This long-term digital archiving or rapid transmission is prohibitive without the use of image compression to reduce the file sizes. There are two basic types of image compression schemes: The first lossless compression scheme encodes and decodes the data perfectly and the reconstructed image matches exactly with the original image, which means there is no loss of data with no degradation. The final decompressed image must be visually lossless and consist of removing the redundant information in adjacent pixels to minimize the number of bits [7,8,9]
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