Compression of medical images for remote diagnosis based on geometric transforms
Sujitha Juliet, Elijah Blessing Rajsingh, Kirubakaran Ezra · International Journal of Telemedicine and Clinical Practices · 2015
With the tremendous growth in imaging applications and the development of filmless radiology, the need for medical image compression becomes essential. This paper proposes a simple method for medical image compression using geometric spatial transforms. The proposed method makes use of the advantage of image scaling that stretches the image region by an adjustable scaling factor to view the particular region of an image. This method also considers the relationship between neighbouring pixels through bilinear interpolation to preserve the visual quality of the image. The dependencies between the geometric transformed coefficients are exploited using set partitioning in hierarchical trees (SPIHT) encoder. Experimental results on a set of medical images demonstrate that besides having better visual quality for the selected region of interest, the proposed method provides competing performance compared with the conventional and state-of-the-art image compression methods, in terms of peak signal to noise ratio and computational time.