We propose a novel coplanar filter, which exploits the coplanarity of gray-level distribution of neighboring pixels, to pre-filter the document images. Experiments show that the proposed filter exhibits the following desired properties for document image binarization: (1) impulsive noise removal, (2) piecewise smoothing, and (3) sharp edge preservation.

introduction: filtering can greatly affect the quality of clinical images. determining the best filter and the proper degree of smoothing can help to ensure the most accurate diagnosis. methods: forty five patient’s data aquired during brain phantom spect studies were reconstructed using filtered back-projection technique. the ramp, shepp-logan, cosine, hamming, hanning, butterworth, metz and w...

texture image analysis is one of the most important working realms of image processing in medical sciences and industry. up to present, different approaches have been proposed for segmentation of texture images. in this paper, we offered unsupervised texture image segmentation based on markov random field (mrf) model. first, we used gabor filter with different parameters’ (frequency, orientatio...

The difficulty of preserving edges is central to the problem of smoothing images. The main problem is that of distinguishing between meaningful contours and noise, so that the image can be smoothed without loss of details. Substantial efforts have been devoted to solving this difficult problem, and a plethora of filtering methods have been proposed in the literature. Non-linear filters have pro...