Reem Kord, Heba Afify* and Manal Abdel Wahed Pages 969 - 975 ( 7 )
Background: Image compression is an area of research that has many applications spanning different technological fields; among the most important of these fields is that of mammography images compression. With whole mammography images becoming increasingly practical and cost-effective, the need for a superior space-saving algorithm is obvious. Also, it becomes important that reconstructed image achieves high compression rates without any alterations from its original form in order to maintain the image quality which has an influence on the accuracy of radiologist diagnosis.
Methods: This paper presents a lossless compression algorithm that is based on image enhancement, Haar wavelet transform and differential Pulse Code Modulation (DPCM) to optimize the compression of 50 mammography images. Image enchantment is implemented by two techniques; Histogram Equalization (HE) and top-hat filtering. The performance of compressed images is measured by Compression Ratio (CR), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and time consumption.
Results: This proposed algorithm is compared to existing ones and the results show that the compression ratio has increased from 6.44 to 26.841.
Mammography images compression, image enchantment, Histogram Equalization (HE), top-hat filtering, Haar wavelet transform, Differential Pulse Code Modulation (DPCM).
Department of Biomedical Engineering, Cairo Higher Institutes for Engineering, Computer Sciences & Management, Cairo, Department of Bioelectronics Engineering, MTI University, Cairo, Department of Systems and Biomedical Engineering, Faculty of Engineering, Cairo University, Cairo