A Multiresolution Hierarchical Approach to Image Segmentation Based on Intensity Extrema
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmenting focused objects in complex visual images
Pattern Recognition Letters
Introduction to data compression (2nd ed.)
Introduction to data compression (2nd ed.)
Unsupervised Multiresolution Segmentation for Images with Low Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
SPWHOS '97 Proceedings of the 1997 IEEE Signal Processing Workshop on Higher-Order Statistics (SPW-HOS '97)
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Segmenting a low-depth-of-field image using morphological filters and region merging
IEEE Transactions on Image Processing
Hierarchical morphological segmentation for image sequence coding
IEEE Transactions on Image Processing
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The popularity of multimedia applications has resulted in development of lossless and lossy compression techniques. This paper presents a novel lossy compression scheme for the low depth-of-field (DOF) images where the quality factor is altered based on whether we are compressing object-of-interest (OOI) or the background. The proposed method involves segmentation of OOI and then the application of lossy scheme. The experimental results shows that the proposed method performs well in compressing the given image (higher compression ratio), at the same time maintaining the acceptable quality (high PSNR).