MATLAB Image Compression using 2D DWT

Problem Definition

Problem Description: Existing image compression techniques based on separable 2D discrete wavelet transform (DWT) fail to provide an efficient representation for directional image features that are not aligned vertically or horizontally, such as edges and lines. These techniques spread the energy of these features across sub bands, leading to loss of important visual information and reduced image quality. As a result, there is a need for an improved image compression technique that can better preserve directional image features and achieve higher compression ratios without significant loss of image quality.

Proposed Work

The proposed work titled "Discrete Wavelet Transform (DWT) based Image Compression using MATLAB" aims to implement the image compression technique of discrete wavelet transform. The project will focus on addressing the limitations of the conventional separable transform by exploring the directionality of image features such as edges and lines. This will be achieved by analyzing parameters like Peak Signal to Noise Ratio, Mean Square Error, and Bit Error Rate. The modules used include Relay Driver (Auto Electro Switching) using Optocoupler, Robotic Arm, Rain/Water Sensor, Basic MATLAB, and MATLAB GUI. The project falls under the categories of Image Processing & Computer Vision, M.

Tech | PhD Thesis Research Work, and MATLAB Based Projects, with subcategories including Image Compression and MATLAB Projects Software. This research work will contribute to further advancements in image compression techniques utilizing the power of discrete wavelet transform.

Application Area for Industry

This project can be used in various industrial sectors such as medical imaging, surveillance, satellite imaging, and remote sensing. These industries often deal with large amounts of image data that need to be compressed for storage and transmission purposes. The proposed solution of implementing discrete wavelet transform to better preserve directional image features can help in maintaining the quality of critical visual information such as edges and lines in these images. By achieving higher compression ratios without significant loss of image quality, this project can address the challenge of efficiently storing and transmitting large image datasets in industries where image quality is crucial. Implementing these solutions can lead to benefits such as reduced storage requirements, faster transmission speeds, and improved overall image quality in various industrial domains.

Application Area for Academics

The proposed project on "Discrete Wavelet Transform (DWT) based Image Compression using MATLAB" holds great potential for research by MTech and PhD students in the field of Image Processing & Computer Vision. By addressing the limitations of existing image compression techniques based on separable 2D DWT, this project offers a valuable opportunity for researchers to explore innovative methods for preserving directional image features such as edges and lines. MTech and PhD students can utilize the code and literature of this project to conduct simulations, data analysis, and experimental studies for their dissertations, theses, or research papers. The project's focus on parameters like Peak Signal to Noise Ratio, Mean Square Error, and Bit Error Rate provides a solid foundation for evaluating the effectiveness of the proposed image compression technique. By incorporating modules like Relay Driver (Auto Electro Switching), Robotic Arm, Rain/Water Sensor, and MATLAB GUI, students can engage in hands-on experimentation and develop practical solutions to enhance image compression performance.

The interdisciplinary nature of this project, spanning across Image Processing, Computer Vision, and MATLAB technologies, offers a diverse range of research opportunities for scholars specializing in these domains. The future scope of this project includes exploring advanced algorithms, optimizing compression ratios, and integrating real-time image processing applications. Overall, the proposed project enables MTech and PhD students to contribute to the advancement of image compression techniques through innovative research methods and practical implementations.

Keywords

Image Compression, Discrete Wavelet Transform, DWT, Directional Image Features, Image Quality, Compression Ratios, MATLAB, Peak Signal to Noise Ratio, Mean Square Error, Bit Error Rate, Relay Driver, Auto Electro Switching, Optocoupler, Robotic Arm, Rain Sensor, Water Sensor, MATLAB GUI, M.Tech Thesis, PhD Thesis, Research Work, Image Processing, Computer Vision, MATLAB Projects Software, Image Acquisition, Linpack, DCT, Encoding, Huffman, RLE, LZW, JPEG 2000, Lossless Compression, Lossy Compression.