# Category: Image Processing

Image Processing

## Histogram Equalization in OpenCV

What is an Image Histogram It is a graphical representation of the intensity distribution of an image. It quantifies the number of pixels for each intensity value considered. What is Histogram Equalization It is...

## Sobel Operator

The Sobel operator is an algorithm for edge detection in images. Edge detection for those who are not familiar with the term, is an image processing technique to discover the boundaries between regions in...

## Detecting corners of image using Non-Maximum Suppression

Non-maximum supression is often used along with edge detection algorithms. The image is scanned along the image gradient direction, and if pixels are not part of the local maxima they are set to zero....

## Median Filtering

The median filter is normally used to reduce noise in an image, somewhat like the mean filter. However, it often does a better job than the mean filter of preserving useful detail in the...

## Gaussian Blur Filter

The Gaussian blur filter is the best-known example of a LPF implemented with a nonuniform kernel. The mask coefficients for the Gaussian blur filter are samples from a 2D Gaussian function : The parameter...

## Mean Filtering

The mean (also known as neighborhood averaging) filter is perhaps the simplest and most widely known spatial smoothing filter. It uses convolution with a (usually 3 ×3) mask whose coefficients have a value of...

## Standard examples of Convolution Masks

Image filtering allows you to apply various effects on photos. The type of image filtering described here uses a 2D filter similar to the one included in Paint Shop Pro as User Defined Filter...

## Convolution in the Two Dimensional Domain

The mathematical definition for 2D convolution is : In practice, this is rewritten as : where m2 is equal to half of the mask’s width and n2 is equal to half of the mask’s...

## Convolution in the One Dimensional Domain

Convolution is a widely used mathematical operator that processes an image by computing—for each pixel—a weighted sum of the values of that pixel and its neighbors. Depending on the choice of weights, a wide...

## Neighborhood Processing

Neighborhood-oriented operations perform techniques are those image processing techniques in which the resulting value for a pixel at coordinates (x0, y0)—which we shall call the reference pixel—is a function of the original pixel value...

## Contrast stretching

One of the simplest piecewise linear functions is a contrast-stretching transformation. Low-contrast images can result from poor illumination, lack of dynamic range in the imaging sensor, or even wrong setting of a lens aperture...

## Local enhancement using histogram statistics

This method is used to enhance details over small areas in an image. The procedure is to define a square or rectangular neighborhood and move the center of this area from pixel to pixel....

## Histogram equalization

This method usually increases the global contrast of images, especially when the usable data of the image is represented by close contrast values. Through this adjustment, the intensities can be better distributed on the...

## Power Law transformation

The general form of Power Law transformation is : s = c * r Ɣ Where c,Ɣ positive constants power-law curves with fractional values of Ɣ map a narrow range of dark input values...

## MATLAB Classes

There are many different data types, or classes, that you can work with in the MATLAB® software. You can build matrices and arrays of floating-point and integer data, characters and strings, and logical true...

## Contrast enhancement using Logarithmic transformation

The general for m is : S = C * LOG( 1+R ) where S is the output value R is the input value C is a constant This transformation maps a narrow range...