Advanced film grain noise extraction and synthesis for high-definition video coding
IEEE Transactions on Circuits and Systems for Video Technology
Lossy compression of noisy images based on visual quality: a comprehensive study
EURASIP Journal on Advances in Signal Processing
Approaches to classification of multichannel images
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Lossy compression of images with additive noise
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
Processing and classification of multichannel remote sensing data
MICAI'11 Proceedings of the 10th international conference on Artificial Intelligence: advances in Soft Computing - Volume Part II
| Hi-index | 0.01 |
Noise degrades the performance of any image compression algorithm. This paper studies the effect of noise on lossy image compression. The effect of Gaussian, Poisson, and film-grain noise on compression is studied. To reduce the effect of the noise on compression, the distortion is measured with respect to the original image not to the input of the coder. Results of noisy source coding are then used to design the optimal coder. In the minimum-mean-square-error (MMSE) sense, this is equivalent to an MMSE estimator followed by an MMSE coder. The coders for the Poisson noise and the film-grain noise cases are derived and their performance is studied. The effect of this preprocessing step is studied using standard coders, e.g., JPEG, also. As is demonstrated, higher quality is achieved at lower bit rates