04-05-2017, 05:31 PM
Hi am YOHANNES i would like to get details on java source code for image compression using dwt ..My friend SAMUEL said java source code for image compression using dwt will be available here and now i am living at BAHIRDAR UNIVERSITY and i last studied in the college/school BAHIRDAR UNIVERSSITY and now am doing IMAGE COMPRESSION PROJECTS AND I NEED A HELP NOW.
Hi am YOHANNES i would like to get details on java source code for image compression using dwt ..My friend SAMUEL said java source code for image compression using dwt will be available here and now i am living at BAHIRDAR UNIVERSITY and i last studied in the college/school BAHIRDAR UNIVERSSITY and now am doing IMAGE COMPRESSION PROJECTS AND I NEED A HELP NOW.
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Wavelet transformations are essential tools to make sense of the world (AKA signal processing). The term signal refers to any flow of information that varies according to one or more range variables. Very often, in signal processing literature, the range variable is time, but it could be essentially anything: position, applied magnetic field, wavelength or even a dimensionless sequence. In applications, the function can be a recorded sound, an image, a transducer response, an EKG or MRI, spectrometry data, weather records, chaos, etc. The list is endless and there are countless creative opportunities for developers to explore new approaches to data analysis using wavelets. A very active dicipline is the pattern recognition based on the machine.
In this paper we provide an application that uses discrete wavelet transformations to explore one-dimensional signals. The focus can be further developed to transform signals with higher dimensions, such as images. There are other ways to add wavelet functionality to Java, such as the use of Matlab / Scilab-Wavelab containers or open source libraries. For example, I chose to present the fundamentals of calculations directly in Java methods.
The computational classes in this project are translations of the C # code I wrote a couple of years ago. Investing the process should be fairly easy.
Ideally, an image compression technique removes redundant and / or irrelevant information, and efficiently encodes what remains. Image compression is most important for efficient transmission and image storage space. Image compression plays a more powerful role in digital image processing. In this work the DWT and Vector quantification technique is simulated. Using different codebook sizes, we apply the DWT-VQ and Extended DWT-VQ technique (which is the modification algorithm) in several types of images.