On the Representation of Image Structures via Scale Space Entropy Conditions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards a multi-modal perceptual model
BT Technology Journal
BT Technology Journal
Telepresence: Understanding People as Content
Presence: Teleoperators and Virtual Environments
Edge Enhancement Post-processing Using Hopfield Neural Net
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Characterization of image distortions in multi-camera systems
Proceedings of the 2nd International Conference on Immersive Telecommunications
A novel perceptual quality metric for video compression
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Optimization of spatial error concealment for H.264 featuring low complexity
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
Content-partitioned structural similarity index for image quality assessment
Image Communication
A new perceptual quality metric for compressed video based on mean squared error
Image Communication
Wavelet-based directional structural distortion model for image quality assessment
Pattern Recognition and Image Analysis
Perceptual motivated coding strategy for quality consistency
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Edge-guided resolution enhancement in projectors via optical pixel sharing
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Fuzzy logic and temporal information applied to video quality assessment
Journal of Mobile Multimedia
Hi-index | 0.01 |
Some psychovisual properties of the human visual system are discussed and interpreted in a mathematical framework. The formation of perception is described by appropriate minimization problems and the edge information is found to be of primary importance in visual perception. Having introduced the concept of edge strength, it is demonstrated that strong edges are of higher perceptual importance than weaker edges (textures). We have also found that smooth areas of an image influence our perception together with the edge information, and that this influence can be mathematically described via a minimization problem. Based on this study, we have proposed to decompose the image into three components: (i) primary, (ii) smooth, and (iii) texture, which contain, respectively, the strong edges, the background, and the textures. An algorithm is developed to generate the three-component image model, and an example is provided in which the resulting three components demonstrate the specific properties as expected. Finally, it is shown that the primary component provides a superior representation of the strong edge information as compared with the popular Laplacian-Gaussian operator edge extraction scheme