CT and MRI image compression using wavelet-based contourlet transform and binary array technique

Compression techniques are essential for efficient storage and fast transfer of medical image data. In this paper, a rapid 2-D lossy compression technique constructed using wavelet-based contourlet transform (WBCT) and binary array technique (BAT) has been proposed for computed tomography (CT) and magnetic resonance imaging (MRI) images. In WBCT, the high-frequency subband obtained from wavelet transform is further decomposed into multiple directional subbands by directional filter bank to obtain more directional information. The relationship between the coefficients has been changed in WBCT as it has more directions. The differences in parent–child relationships are handled by a repositioning algorithm. The repositioned coefficients are then subjected to quantization. The quantized coefficients are further compressed by BAT where the most frequently occurring value is coded only once. The proposed method has been experimented with real-time CT and MRI images, the results indicated that the processing time of the proposed method is less compared to existing wavelet-based set-partitioning in hierarchical trees and set-partitioning embedded block coders. The evaluation results obtained from radiologists indicated that the proposed method could reproduce the diagnostic features of CT and MRI images precisely.