Image enhancement with the application of local and global enhancement methods for dark images

1. Venkat Java Projects
Mobile:+91 9966499110
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Image Enhancement with the Application of Local and Global
Enhancement Methods for Dark Images
Image enhancement techniques have been widely used in many applications of image processing
where the subjective quality of images is important for human interpretation. Contrast is an
important factor in any subjective evaluation of image quality. Contrast is created by the difference
in luminance reflected from two adjacent surfaces. In other words, contrast is the difference in
visual properties that makes an object distinguishable from other objects and the background. In
visual perception, contrast is determined by the difference in the colour and brightness of the object
with other objects. Our visual system is more sensitive to contrast than absolute luminance;
therefore, we can perceive the world similarly regardless of the considerable changes in
illumination conditions. Many algorithms for accomplishing contrast enhancement have been
developed and applied to problems in image processing.
In this Project We have used HSV, Histogram Equalization and Contrast Image Processing to
enhance the images.
HSV Color Model:
HSV color system is based on the Hue shift, Saturation and Value. Unlike the RGB color system,
which has to do with "implementation details" regarding the way RGB displays color, HSV has to
do with the "actual color" components. Another way to say this would be RGB is the way
computers treats color, and HSV try to capture the components of the way we
humans perceive color.
The main reason to work on the HSV version of an image is because using Hue component makes
the algorithms less sensitive (if not invariant) to lighting variations.
Histogram Equalization
Histogram Equalization is a computer image processing technique used to improve contrast in
images. It accomplishes this by effectively spreading out the most frequent intensity values, i.e.
stretching out the intensity range of the image. This method usually increases the global contrast of
images when its usable data is represented by close contrast values. This allows for areas of lower
local contrast to gain a higher contrast.
A color histogram of an image represents the number of pixels in each type of color component.
Histogram equalization cannot be applied separately to the Red, Green and Blue components of the
image as it leads to dramatic changes in the image’s color balance. However, if the image is first
converted to another color space, like HSL/HSV color space, then the algorithm can be applied to
the luminance or value channel without resulting in changes to the hue and saturation of the image.
CAIP:
A color histogram of an image represents the number of pixels in each type of color component.
Histogram equalization cannot be applied separately to the Red, Green and Blue components of the
image as it leads to dramatic changes in the image’s color balance. However, if the image is first
converted to another color space, like HSL/HSV color space, then the algorithm can be applied to
the luminance or value channel without resulting in changes to the hue and saturation of the image.

2. Venkat Java Projects
Mobile:+91 9966499110
Visit:www.venkatjavaprojects.com Email:venkatjavaprojects@gmail.com
Execution Steps:
Double Click on run.bat file on your folder location.
Above screen will be opened and Now upload the Dark imges by click on “Upload Dark
Images”.

3. Venkat Java Projects
Mobile:+91 9966499110
Visit:www.venkatjavaprojects.com Email:venkatjavaprojects@gmail.com
Select the file to enhance from the testdata file.
Uploaded Image will be displayed on the window. Now Click on the Enhance Button.
Ehanced Image will be displayed on the new window.