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Key Features Of Image Enhancement

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A. Image enhancement Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further image analysis. For example, you can remove noise, sharpen, or brighten an image, making it easier to identify key features. Image enhancement mainly includes some process: A.1 Convert a Colored Image into Gray Image Every digital image mainly comprises of three components or it is made up of three colors that is RGB (Red Green and Blue) and each image is represented in a 3-dimensional which is very difficult to analysis and process. Therefore to overcome some difficulty initially each image is first converted into a gray image which is made up of white and black components of varying intensity. …show more content…

So on, it moves until the end of a column and calculate the total sum of differences between adjacent pixels. At the end, an array containing the column-wise sum is created. The same process is carried out to find the vertical array. In this case, rows are processed instead of columns. A.4 Filtering out Unwanted Regions in an Image Once the arrays are passed through a low-pass digital filter, a filter is applied so that to remove undesirable areas from an image which includes the horizontal and vertical components of array with low values. Generally low value indicates the plain areas with characters it is due to the fact that intensity of each neighboring pixel of plain areas contains a similar intensity or pixel values such that during horizontal and vertical processing the difference between them is negligible but in case of edges and specially numeric characters the difference between adjacent pixel is high due to variation of intensity, which results into a high array value for such part of an image. Therefore, the required area of region of interest with probable number has a high values while areas with small value are undesirable and such regions are filtered out by applying a certain threshold. In this algorithm, the threshold is equal to the average value of an array. Both row and column vectors are passed through a filter with this threshold, so that the final output

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