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Digital image processing is the use of a digital computer to process digital images through an algorithm. [1] [2] ... Gonzalez, Rafael C.; Woods, Richard E. (2008).
In most cases in image processing thickening is performed by thinning the background [1] (,) = () where ∪ {\displaystyle \cup } denotes the set-theoretical difference and ⊙ {\displaystyle \odot } denotes the hit-or-miss transform , and B i {\displaystyle B_{i}} is the structural element and X {\displaystyle X} is the image being operated on.
According to figures one to four, we can see how homomorphic filtering is used for correcting non-uniform illumination in the image, and the image become clearer than the original. On the other hand, if we apply the high pass filter to the homomorphic filtered image, the edges of the images become sharper and the other areas become dimmer.
Each pixel of the output image at point (x,y) is given by the product of the pixels within the geometric mean mask raised to the power of 1/mn. For example, using a mask size of 3 by 3, pixel (x,y) in the output image will be the product of S(x,y) and all 8 of its surrounding pixels raised to the 1/9th power.
An Introduction to Morphological Image Processing by Edward R. Dougherty, ISBN 0-8194-0845-X (1992) Morphological Image Analysis; Principles and Applications by Pierre Soille, ISBN 3-540-65671-5 (1999) R. C. Gonzalez and R. E. Woods, Digital image processing, 2nd ed. Upper Saddle River, N.J.: Prentice Hall, 2002.
The pruning algorithm is a technique used in digital image processing based on mathematical morphology. [1] It is used as a complement to the skeleton and thinning algorithms to remove unwanted parasitic components (spurs). In this case 'parasitic' components refer to branches of a line which are not key to the overall shape of the line and ...