Contrast manipulation

Contrast stretching is a common image enhancement technique in remote sensing used to improve the visual quality and interpretability of satellite or aerial imagery. It involves expanding the range of pixel values in an image, typically by remapping the original values to a new range. This process enhances the visual contrast between different features in the image.

1. Linear Contrast Stretching:

   Linear contrast stretching is the simplest form of contrast stretching. It involves applying a linear transformation to the pixel values in the image. The transformation stretches the original range of pixel values to a new range. This is typically done using the following formula for each pixel in the image:

   

   NewPixelValue = (OriginalPixelValue - MinOriginalValue)  (NewMaxValue - NewMinValue) / (MaxOriginalValue - MinOriginalValue) + NewMinValue

   - `OriginalPixelValue` is the value of the pixel in the original image.

   - `MinOriginalValue` and `MaxOriginalValue` are the minimum and maximum pixel values in the original image.

   - `NewMinValue` and `NewMaxValue` are the desired minimum and maximum values for the stretched image.

   Linear contrast stretching can improve the overall brightness and contrast of the image.

2. Nonlinear Contrast Stretching:

   Nonlinear contrast stretching is more advanced and allows for greater flexibility in enhancing specific image features. Unlike linear stretching, it involves applying a nonlinear transformation to the pixel values. Various functions, such as logarithmic, power-law, or histogram equalization, can be used for this purpose.

   - Logarithmic Stretching: This method enhances the lower end of the pixel value range more than the higher end, which can be useful for revealing details in dark areas of the image.

   - Power-law (Gamma) Stretching: It allows you to control the degree of stretching using a parameter called the gamma value. A higher gamma value increases the contrast in brighter areas, while a lower gamma value increases contrast in darker areas.

   - Histogram Equalization: This technique redistributes the pixel values in such a way that the cumulative distribution function of the image becomes more uniform. It can enhance local contrast and reveal fine details.

Nonlinear contrast stretching methods are often preferred when specific image features need to be emphasized or when there are non-uniform lighting conditions in the image. The choice between linear and nonlinear stretching depends on the characteristics of the image and the objectives of the analysis in remote sensing applications.