This document discusses various image enhancement techniques. It begins by defining image enhancement as a process to improve image quality, clarity, and visual appearance by correcting issues like low contrast, poor lighting, noise, and other imperfections. It then provides examples of enhancing by adjusting brightness and contrast. The document classifies enhancement techniques into spatial and frequency domains. Spatial techniques directly modify pixel values, while frequency techniques use Fourier transforms and operate in the frequency domain. Specific spatial techniques mentioned include pixel transformation, image inverse, power law transformation, and log histogram equalization. Pixel transformation and image inverse are then described in more detail.

1. IMAGE ENHANCEMENT TECHNIQUES
Mehak Parvaiz
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2. Image Enhancement
• Image enhancement is a process of improving the
quality,clarity, and visual apperance of an digital image.
• Image enhancement aim is to correct issues such as low
contrast, poor lighting,noise, and other imperfections.
• Image enhancement is required for the image processing so
that image analysis can be done accurately.

3. Example:
When we click image, sometimes the image is not very much
clear, so we try to increase the brightness, reduce the
brightness and varying the contrast as well.The process via
which we are improving quality of image is known as image
enhancement.
If the captured image is not of good quality then it needs to
be enhanced. Quality degredation may be because of the
noise, poor brightness, contrast, blur etc.

4. Image enhancenent is broadly classified into:
a) Spatial domain
b) Frequency domain
SPATIAL DOMAIN:
• In the spatial domain, we analyze images directly based on
the values of their pixels.
• In the spatial domain, we modify the pixel values of the
image directly to achieve our desired result.
• In the spatial domain, we perform operations like edge
detection, filtering, thresholding and morphological
operations.

5. FREQUENCY DOMAIN:
• The frequency domain images are analyzed in terms of their
frequency components(Amplitude, Phase).
• Fourier transform is used to convert the image from the
spatial domain into the frequency domain.
• In frequency domain, we perform operations like, smoothing,
sharpening,and noise reduction of the image.

6. Image Enhancement Techniques:
• Pixel Transformation.
• Image Inverse.
• Power Law Transformation.
• Log Histogram Equalization.
• Contrast Stretching.

7. Pixel Transformation
• Pixel transformation is a fundamental concept in image
processing.
• Pixel transformation involves modifying the intensity values
of individual pixels in an image to improve its visual quality.
• This technique is commonly used to adjust brightness,
contrast, sharpness and more.

8. The general pixel transformation function can be represented as:
g(x,y)=T[f(x,y)]
Where:
f(x,y) represents the input pixel intensity at coordinates (x,y) in
the orginal image.
g(x,y) represents the transformed pixel intensity at the same
coordinates.
T[..] is the transformation function applied to f(x,y).

9. Image Inverse
• Image inverse is a simple image processing technique that
involves inverting the intensity values of each pixel in an
image.
• In this technique, dark areas become light and light areas
become dark.
• While this might not always improve the visual quality, it can
be used creatively to produce artistic or dramatic effects.
• This image inverse process is achieved through a
mathematically operation called “negation”.

10. The general image transformationg(x,y) can be defined as:
g(x,y)=max-Intensity-f(x,y)
Where:
f(x,y) represents the input pixel intensity at coordinates (x,y) in
the orginal image.
max-Intensity is the maximum possible pixel intensity value in
the image.

11. THANK YOU