10/11/2018 09:04

Digital Image Processing, Edge-direction (HASH Method)

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Digital Image Processing, Edge-direction (HASH Method)

Many interpolation methods for high visual quality have been developed in image processing and problems still exist. These problems are highly related to image edges, including the blurring of edges, Blocking artifacts in diagonal directions and inability to generate fine details.

In medical field, Image Interpolation is required in a variety of medical image processing applications. Although many interpolation techniques are known from the literature, evaluations of these techniques for the specific task of applying geometrical transformations to medical images are still lacking.

I proposed a new image interpolation (Hash Method) which takes geometric duality to estimate covariance of targeted High Resolution(HR) area from that a pixels in Low Resolution (LR).

The Major Advantage of interpolation techniques is that it may cost less and the existing equipments can be utilized. To magnify a region of interest in surveillance, forensic, scientific, medical imaging has been proven useful in many practical cases.

HASH Method:
HASH (#) Method have been adopted to generate clarity image process where 5×5 matrix is utilized. Current pixel is taken for the processing so that we can avoid mixing of neighbour colour. 
Blurred images are exhibited when colour is mixed with others.

HASH (#) method is unique method to control blur at the same time it maintains shape and as it is retain the clarity. 

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