Research And Implementation Of Underwater Acoustic Image Fractal Compression Coding Technology

With the development of computer technology, communication technology and internet technology, people receive and send a lot of information every day through computer and mobile devices. Multimedia information being intuitive, carried by large amount of information, but the amount of data, storage space should not be underestimated. The storage device cannot satisfy the more and more multimedia information storage requirements, and image compression is one of the main ways to solve the image transmission and storage.Fractal compression coding, technology is the representative of the image compression coding technology. This coding method with better compression ratio, gets the high quality of the decoded image also. Because of the complexity of the code and long encoding time, fractal coding technique has not been widely accepted and the scope of its application is limited. The fractal code of these problems is prompted because scientists and scholars continue to study,and at present, there are a lot of fractal coding algorithm is proposed.Underwater acoustic image is the effective way to obtain the terrain and target under the water for people. With the continuous development of acoustic imaging technology, people's demand of the underwater acoustic image is becoming more and more. The particularity of the underwater environment results in underwater acoustic image resolution being too low,and people care about the underwater target submerged in the background with the underwater noise and reverberation. The image content is often bottom topography and small targets, so the fractal compression algorithm is suitable for the irregular target. For such images, image compression ratio is very high. In this paper, the fractal image compression processing method is introduced into the underwater acoustic image processing system, and compared with the traditional image compression methods, then the new algorithm under the precondition ensures the underwater acoustic image quality and higher image compression ratio.In this paper, the fractal algorithm and Huffman coding, prediction coding, discrete cosine transform coding are compared to show the novel idea of fractal image coding,decoding time characteristics. The effects of different codebook sizes and segmented image blocks on the decoded images are compared with the basic fractal algorithm, and the influence factors of fractal encoding, time and decoding time are analyzed, By researching the relationship between fractal number of iterations and the quality of the decoded image,combining the gray level difference method for fast fractal image coding algorithm based on proposed improvements, the introduction of two control parameters are used to control the speed and quality of image coding. With the image block horizontal and vertical variance ratio as the condition, we find a new eliminating condition to further reduce the scope of the code, which overcomes the shortcomings of the basic fractal algorithm with a large amount of matching computation and long time of encoding. The new algorithm ensure the quality of the reconstruction image and improve the speed of encoding.In order to further improve the quality of underwater acoustic image decoding,underwater acoustic image pre-processing including median filter, gaussian filter and wiener filter technology is studied to test underwater acoustic image processing ability. The experimental data show that the three kinds of filter can effectively improve the acoustic image fractal compression coding of the reconstructed image quality and improve the signal-to-noise ratio of the reconstructed image. By using wiener filtering pre-processing, the fractal decoding acoustic image signal-to-noise ratio is the highest, and by using gaussian filtering pre-processing, the underwater acoustic image coding time is the shortest. This paper finally realizes the fast fractal compression in underwater acoustic image processing functions,and the feasibility and effectiveness of the new algorithm are verified in the aspect of underwater acoustic image fractal compression processing.