The document discusses various methods for enhancing image quality through image editing processes. It details techniques such as filtering with morphological operators, noise removal, and contrast adjustments, allowing users to modify specific image properties according to their needs. Users can ultimately save their enhanced images while maintaining the original raster image file.

1. image enhancement projects

2. ARTICLE
• Image editing encompasses the processes of altering images, whether they are digital photographs,
traditional analog photographs, or illustrations. Traditional analog image editing is known as photo
retouching, using tools such as an airbrush to modify photographs, or editing illustrations with any
traditional art medium.
• In this project we will enhance the quality of an image on basis of various properties of image as
discussed above in the introduction so that the quality of the image get enhanced and can be used
at various application with enhanced properties. We will select an image from user whose quality is
to enhance.
• Next step is to change the specific property of image as many options are given to the user. After
that there is save option for user to save enhanced image as per user need.
• You can adjust brightness, contrast, and fade for the display of an image as well as for plotted
output without affecting the original raster image file
• 1.Filtering with morphological operators.
• 2.Histogram equalization.
• 3.Noise removal using a Wiener filter.
• 4.Linear contrast adjustment.
• 5.Median filtering.
• 6.Unsharp mask filtering.
• 7.Contrast-limited adaptive histogram equalization (CLAHE)
• 8.Decorrelation stretch.