Image Coding For Aestentically Acceptable Distortion Using Depth Blurring
C.Yaminika1, M.Vijayalaxmi2
1C.Yaminika, Department of DECS, Sri Kalahasteeswara institute of technology, Srikalahasti, Chittoor (Andhra Pradesh), India.
2M.Vijayalaxmi, Assistant Prof., Department of ECE, Sri Kalahasteeswara Institute of Technology, Srikalahasti, Chittoor (Andhra Pradesh), India.
Manuscript received on 18 August 2012 | Revised Manuscript received on 25 August 2012 | Manuscript published on 30 August 2012 | PP: 180-182 | Volume-1 Issue-3, August 2012 | Retrieval Number: C0297071312/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Realistic simulation of distance blurring, with the desirable properties of aiming to mimic occlusion effects as occur in natural blurring, and of being able to handle any number of blurring and occlusion levels with the same order of computational complexity will help in compressing the image. Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. This is because lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate. The lossy compression that produces imperceptible differences may be called visually lossless. the concept of depth-based blurring to achieve an aesthetically acceptable distortion when reducing the bitrate in image coding is proposed which is vital in lossless image compression. Depth-based blurring reduces high-frequency components by mimicking the limited depth of field effect that occurs in cameras. The Proposed algorithm performs better than the existing spatial domain methods, significantly to cope with the challenge of avoiding intensity leakage at the boundaries of objects when blurring at different depth levels.
Keywords: Image Coding, Depth Blurring.
Scope of the Article: Image Processing