This document discusses image processing techniques including image formats, applications, enhancement, watermarking, analysis, compression, and preprocessing. It introduces MATLAB as a tool for technical computing and image processing. Common image formats are described like JPG, GIF, TIFF, PNG, and BMP. Key image processing techniques covered are enhancement through adjusting light/dark levels, contrast, and filtering noise; watermarking to embed secret images; analysis to extract information; and compression to reduce image size for storage and transmission. Preprocessing is used to standardize intensities and remove noise before further analysis.

1. Application Of Image
Processing Techniques

2. Contents:
1. MATLAB introduction
2. Image Processing Basic Formats of Image, Colour
3. Techniques

3. Introduction:
* MATLAB -> Matrix Laboratory
* Developed by Cleve Moler in 1984 as a teaching tool
* High performance language for technical computing
* Typical uses are,
1. numerical computation
2. Data analysis ,plotting and visualization
3. Graphical user interface building
4. Algorithm development and modelling

4. IMAGE PROCESSING:
* Image –It is define as the group of pixels.
* Image formats:
1. JPG/.JPEG - Joint Photographic Experts Group
2. GIF - Graphics Interchangeable Format
3. TIFF - Tagged Image File Format
4. PNG - Portable Network Graphics
5. BMP - Bitmap format
o Applications of image processing:
1. Research
2. Surveillance
3. Medical

5. IMAGE PROCESSING TECHNIQUES:
1. Image Enhancement
2. water Marking
3. Image Analysis
4. Image Compression

6. Image Enhancement:
*Image Enhancement is the improvement of digital image quality, without
knowledge about the source of degradation.
*To Make an image lighter or darker or to increase or decrease contrast,
pseudo colouring, noise filtering, sharpening and magnifying.
*Programs  image enhancements -> image editors.
*The aim of image enhancement is to improve the interpretability or
perception of information in image.
Examples:
*Noise Smoothing.
*Contrast Manipulation.

7. WATER MARKING:
* Water Marking – Embed the secret image in an image or any type of
multimedia data.
* We should hide the image without changing original image quality.
* Water marking is used only for copyright protection
* The applications of water marking are,
1. Tele – broadcasting
2. Web-applications
* There are two types of water marking they are:
• Visible water marking • Invisible water marking

8. Image Analysis:
* Image analysis methods extract information from an image by using
automatic or semiautomatic techniques termed as scene analysis, image
description, image understanding, pattern recognition, computer/machine
vision .
* Image analysis differs from other types of image processing methods, such
as enhancement or restoration in that the final result of image analysis
procedures is a numerical output rather than a picture.

9. Image Processing:
*Preprocessing indicates that the same tissue type may have a different
scale of signal intensities for different images.
* Preprocessing functions involve those operations that are normally
required prior to the main data analysis and extraction of information and are
generally grouped as radiometric or geometric corrections.
*The preprocessed images will have some noise which should be removed
for the further processing of the image.

10. Image Compression:
*The objective of image compression is to reduce the size of digital images
to save storage space and transmission time.
*Lossless compression is preferred for artificial images like technical
drawings, icons and also be preferred for high value content, such as
medical imagery or image scans made for archival purposes.

11. Conclusion:
*Image rectification is the pre-processing of satellite data for geometric and
radiometric connections.
*Display data for subsequent visual interpretation. Information withdrawal is
based on digital classification and is used for generating digital thematic
map.
*This paper presents various techniques of image processing.
*After study of all techniques it is found that lossless image compression
techniques are most effective over the lossy compression techniques.