This document discusses various image enhancement techniques including: - Point operations that deal with pixel values individually such as brightness enhancement, thresholding, and log transformations. - Spatial domain methods that operate directly on pixels including image negative, log transformation, and noise reduction. - Other techniques like image deblurring, filtering, sharpening, and contrast stretching are used to improve aspects of images like brightness, sharpness, and noise reduction.

1. Image enhancement
Group member
Hina, Samreen and Shahida

2. Image Enhancement
• Image enhancement refers to a set of
techniques and processes aimed at improving
the visual quality and overall appearance of an
image. The goal is to enhance specific aspects
of the image, such as brightness, contrast,
sharpness, color accuracy, and noise
reduction, to make it more visually appealing
or suitable for specific applications.

3. Introduction:
• Image Enhancement is the process of manipulating an image so that
the result is more suitable than the original for a specific application.
• The goal is to enhance specific aspects of the image, such as
brightness, contrast, sharpness, color accuracy, and noise
reduction, to make it more visually appealing or suitable for
specific applications.

4. Image enhancement techniques:

5. Spatial domain methods:
• The term spatial domain refers to the aggregate of pixels composing
an image.
• Spatial domain methods are procedures that operate directly on these
pixels.
• Spatial Domain processes will be denoted by the expression ,
g(x,y)= T[f(x,y)]
Where, g is the output, f is the input image and T is an operation on f
defined over some neighborhood of (x,y)

6. Cont…
According to the operations on the image pixels, it can be further
divided into 2 categories:
1. Point operations
2. Spatial operations

7. Point Opeation
 Operation deals with pixel intensity values individually.
 The intensity values are altered using particular transformation
techniques as per the requirement.
 The transformed output pixel value does not depend on any of the
neighbouring pixel value of the input image.
Examples:
 Image Negative.
 Log Transformation
 Thresholding.
 Brightness Enhancement.
 Log Transformation.
 Power Law Transformation
3

8. Image Negtive
 Negative images are useful for enhancing white or grey
detail embedded in dark regions of an image.
 The negative of an image with gray levels in the range
[0,L-1] is obtained by using the expression
s = L -1 - r
L-1 = Maximum pixel value .
r = Pixel value of an image.

9. Cont…
Fig: Example of image inversion

10. Log Transformation
 The log transformation is given by the expression
• s = c log(1 + r)
• where c is a constant and it is assumed that r≥0.
 This transformation maps a narrow range of low- level
grey scale intensities into a wider range of output
values.
 Similarly maps the wide range of high-level grey scale
intensities into a narrow range of high level output values.
 This transform is used to expand values of dark pixels and
compress values of bright pixels.

11. Logarithmic Transformaion Contd…
Original Image Transformed Image

12. Techniques
• Image Deblurring
• Image filtering
• Image sharping
• Noise Reduction
• Contrast enhancement

13. Image Debluring
• Image deblurring refers to the process of
reducing or removing blur from an image to
restore its sharpness and clarity. Blurring in
images can occur due to various factors such
as motion blur, camera shake, defocus blur, or
lens aberrations.

14. Types of image blurring
• Motion Blur
• Defocus Blur

15. Motion blur
• Motion blur occurs due to the relative
movement between the camera and the
subject during exposure.

16. Defocus blurring
Defocus blur is caused by incorrect focus settings
limited depth of field.

17. Image Filtering
• Image filtering is a fundamental technique
used in image processing to modify or
enhance images by applying certain
operations to each pixel or a group of pixels.
– Convolution
– Correlation

18. Noise Reduction
• Noise reduction, on the other hand, is
the process of minimizing or
eliminating unwanted random
variations or distortions that degrade
the quality of an image

19. Image sharping
• Image Sharpening is a technique for
increasing the apparent sharpness of an
image.
• It enhance edges and fine details.

20. Contrast stretching
• Contrast stretching is a simple technique
to enhance the contrast of a digital image
by mapping the pixel values to a wider
range.