Title :
Lossy compression of noisy images
Author :
Al-Shaykh, Osama K. ; Mersereau, Russell M.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fDate :
12/1/1998 12:00:00 AM
Abstract :
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
Keywords :
Gaussian noise; code standards; data compression; image coding; least mean squares methods; quantisation (signal); source coding; telecommunication standards; Gaussian noise; JPEG lossy image compression standard; Lloyd-Max quantisation; MMSE coder; MMSE estimator; Poisson noise; distortion; film-grain noise; image compression algorithm; minimum-mean-square-error; noisy images; noisy source coding; optimal coder design; performance; preprocessing; standard coders; Degradation; Gaussian noise; Image coding; Image storage; Noise level; Noise reduction; Quantization; Source coding; Tomography; Transform coding;
Journal_Title :
Image Processing, IEEE Transactions on
