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The LAT is employed to extract the useful information of the image that had been enhanced by the LTE and separated the foreground from the nonuniform illumination background. An input image is broken into small blocks or local window neighborhoods containing a pixel. This is similar in the LHE, LAT, and LHEAT. Each block is surrounded by a larger block. The input image is defined as X �� RH��W, with dimensions of H �� W pixels, and the enhanced image is defined as Y �� RH��W, with [http://www.selleckchem.com/products/lonafarnib-sch66336.html Lonafarnib cost] H �� W pixels. The input image is then divided into the block Ti = 1,��, n of window neighborhoods with the size w �� w, where w [http://en.wikipedia.org/wiki/VAV2 VAV2] matrix was first rearranged into a 30-column (6 �� 5 = 30) temporary matrix, as shown in Figure 10(b). Each column contained the value of the pixels in its nine-row (3 �� 3 = 9) window. The temporary matrix was then reduced by using the local mean (Mi): Mi=1N��j=1nwj, (2) where w was size of window neighborhoods, j was the number of pixels contained in each neighborhood, i was the number of columns in temporary matrix, and N was the total number of pixels in the block. [http://www.selleckchem.com/screening/tyrosine-kinase-inhibitor-library.html http://www.selleckchem.com/screening/tyrosine-kinase-inhibitor-library.html] After determining the local mean in (2), there was only one row left as shown in Figure 10(c). Subsequently, this row was rearranged into the original shape as shown in Figure 10(d). Figure 10 The sliding neighborhood operation. There are three steps in the LHE technique: the probability density (PD), the cumulative distribution function (CDF), and the mapping function. The probability distribution of image PD for each block can be expressed as follows: Pi=niNfor?i=0,1,��,L?1, (3) where ni is the input pixel number of level, i is the input luminance gray level, and L is gray level, which is 256. Subsequently, the LHE uses an input-output mapping derived from CDF of the input histogram defined as follows: Ci=��i=0nPi. (4) Finally, the mapping function is determined from the CDF as follows: gi=M+xi?M��Ci, (5) where M is the mean value from (2). Although the image has been enhanced, it remains mildly degraded because of the background noise and variation in contrast and illumination. The image was corrupted with two noises, motion blur noise and salt and pepper noise. The median filter, which has a 3 �� 3 mask, was applied over the grayscale image.