Abstract
The huge growth of the usage of internet increases the need to transfer and save multimedia files. Mammogram images are part of these files that have large image size with high resolution. The compression of these images is used to reduce the size of the files without degrading the quality especially the suspicious regions in the mammogram images. Reduction of the size of these images gives more chance to store more images and minimize the cost of transmission in the case of exchanging information between radiologists. Many techniques exists in the literature to solve the loss of information in images. In this paper, two types of compression transformations are used which are Singular Value Decomposition (SVD) that transforms the image into series of Eigen vectors that depends on the dimensions of the image and Discrete Cosine Transform (DCT) that covert the image from spatial domain into frequency domain. In this paper, the Computer Aided Diagnosis (CAD) system is implemented to evaluate the microcalcification appearance in mammogram images after using the two transformation compressions. The performance of both transformations SVD and DCT is subjectively compared by a radiologist. As a result, the DCT algorithm can effectively reduce the size of the mammogram images by 65% with high quality microcalcification appearance regions.
Highlights
The emergence of internet and the vast development of web technologies in addition to the popularity of social networks, image sharing and video application triggered the inevitable need for minimizing the amount of digital information stored and transmitted
This paper will evaluate the performance of two compression techniques: full frame discrete cosine transform (DCT) with entropy coding and singular value decomposition (SVD) on digital mammogram images
This paper presents an ongoing effort to reduce the image size in order to be processed and transmitted through the media
Summary
The emergence of internet and the vast development of web technologies in addition to the popularity of social networks, image sharing and video application triggered the inevitable need for minimizing the amount of digital information stored and transmitted. JPEG uses the discrete cosine transform (DCT) which is one of the most popular techniques used for image compression. Another technique uses the linear approximation of matrices for compression is singular value decomposition (SVD) [4]. This paper will evaluate the performance of two compression techniques: full frame discrete cosine transform (DCT) with entropy coding and singular value decomposition (SVD) on digital mammogram images. The dependence of their efficiency on the compression parameters was investigated.
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