Digital Image Processing using Matlab Projects.
Digital image process involves pattern recognition, analysis and understanding of images. Projects of digital image processing can be done in an excellent manner by using MATLAB. Images are improvised and removed of noise for the sake of human visualization. Many security concepts are used to store and transmit files in and effective manner. These projects also interlink many fields such as video compression and video based tracking. Digital image processing is a sub study of systems and signals concerning images. Projects on Digital image processing using Matlab Projects provide in addition, detailed study of MATLAB simulation tool. This process involves an input image which processed with many algorithms and various techniques and later on the output result is extracted. This output is obtained with the help of Matlab simulation tool.
Compression source coding:
Source coding with the help of bits per pixel allows the image to acquire less than average length. Various types of source coding are available namely.
Arithmetic coding: Non block code is derived through this coding whole sequence of source symbols are needed to assign a single code word. This process falls under lossless compression technique.
Dictionary based coding: Within less time repeated patterns can be derived coding and decoding tables which are used to stream data is framed by dictionary coding.
Variable length coding: It is also known as Huffman coding. The smallest of code symbol number is obtained by variable coding. Tree based on source symbol probabilities is developed using Huffman coding.
Types of digital images:
- Electron Microscope images.
- Gamma X-radio ray images.
- ASTER images.
- Medical images.
- Astronomical images.
- Digital photos.
- Underwater SONAR images.
- Satellite images.
Image compression: In order to include information in an image it is compressed of its size. By this process transmission bandwidth is widened and the transaction is done in a smooth way. Compressions of data are of two types, lossy compression and lossless compression. Few data is lost during lossy compressing leaving free space during storage purpose while lossless compression no data is lost this makes secure transmission possible.
Flow of image compression: The compressed image is processed into a sequence of binary data called as bit stream. Then it is reconstructed and the quantity of data is reduced from its original state. Using RMS (root means square) the performance is measured. Quantization and source coding is required for this compression process
Applications of image compression:
- Tele video conferencing.
- Remote sensing.
- Document and medical imaging.
- Control of remotely piloted vehicles in military.
- Hazardous waste management and space.
- Facsimile transmission.
Application of image processing.
- Medical applications.
- Restoration and Enhancement.
- Standardization on image processing.
- Digital camera.
- Image Transmission and coding.
- High quality color representation.
- Television and tourism.
Image Enhancement:
An image is enhanced by cancelling noises and by making it more visually aesthetic by detailing every portion. Though it enhances details it does not alter any internal data. Types of image enhancement are:
- Frequency Operation.
- Pseudo coloring.
- Point operation.
- Spatial operation.
Frequency Operation:
Fourier Transform method is used by frequency operation to enhance images. It has high- pass and low-pass filtering. Using this image is sharpened and smoothed.
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