This paper proposes an image processing method, named RNAM(Resemble Neighborhood Averaging Method),to facilitate visual data mining,which is used to post-process the data mining result-image and help users to discover significant features and useful patterns effectively.
Comparing eggs image filtered by the methods of dilation and erosion with that did by neighborhood averaging and that did by media filtering, we found media filtering of 3*3 square window was the best choice.
For example, using neighborhood averaging method and median filter method to restrain the image noises and make the image edge smooth, splitting image by threshold mode and image segmentation method based on the edge detection, calculating the area and perimeter of the bottle-flaw image, and using the circularity to judge whether this image is a bottle-flaw image.
In the pretreatment of these images, the Speckle noise model has been improved in this dissertation. On the basis of traditional methods of neighborhood averaging and low-pass filtering, the methods of Adaptive Histogram Enhancement and the improved adaptive Weighted Median Filter have been presented, and the noise has been reduced greatly.
We normalize the kernel matrix before and after the neighborhood averaging operation.
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The low pass filter performed a neighborhood averaging operation for a mask size of 3x3.
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It consists on making a selective neighborhood averaging of the signal.
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In this paper, a new method for image smoothing——the modified neighborhood averaging method is presented. With this method, not only the noise can be smoothed efficiently, but also the blurred edge of an image be sharpened. It is simple in computation, requiring no a priori knowledge and predetermined parameters. In order to evaluate the performance of the proposed method quantitatively, a figure of merit for the test image generated by computer is defined and used as a measure of evaluation. Th...
The properties of X-ray ecxited fluorescent faint image are studied in this paper. Guided byanalyzing the image histogram,using spatial domain processing methods, such as multi-frameaveraging,piecewise linear gray level transformation,neighborhood averaging etc. we have obtainedgood results of noise removing and imageenhancement,and have realized fast image processing.
A Scheme of analysing ultrafine particle picture using digital image processing has been suggested. The technology consists of neighborhood averaging, binarization, reqion splitting, chain codes and shape numbers.