Browsing by Author "Lu, SM"

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A HVS-directed neural-network-based approach for impulse-noise removal from highly corrupted images
(2003)
Lu, SM
;
Pu, HC
;
Lin, CT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper a novel two-stage noise removal algorithm to deal with fixed-value impulse noise is proposed In the first stage, the decision-based recursive adaptive median filter is applied to remove the noise cleanly and keep the uncorrupted information as well as possible. In the second stage, the fuzzy decision rules inspired by human visual system (HVS) are proposed to classify pixels of the image into human perception sensitive class and non-sensitive class. A neural network is proposed to enhance the sensitive regions to perform better visual quality. According to the experiment results, the proposed method is superior to conventional methods in perceptual image quality as well as the clarity and the smoothness in edge regions.
Image blocking artifact suppression by the modified fuzzy rule based filter
(2003)
Chang, JY
;
Lu, SM
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper we propose the modified fuzzy rule-based (MFRB) filter for JPEG-encoded image blocking noise removal. The proposed filter generalizes the FRB filter which is a weighted average of the center pixel and its neighboring pixels in a working window. The weighting coefficients of the MFRB filter depend on the gray level difference, the spatial distance and orientation, and the variance of the pixels in the window. By the least mean square (LMS) learning over representative JPEG-encoded images, the best membership function, i.e., the weight coefficients, of the MFRB filter for blocking noise suppression can be determined. By the simulation results, our proposed scheme has demonstrated the effectiveness and robustness in blocking noise removal. Compared to several post-filtering approaches, our MFRB filter has produced the best SNR improvement among the resultant images. This objective superiority is also confirmed visually by the sharper and more pleasing image obtained.