Evolutionary Design of Multiplierless Lifting-based 2D DWT Filters for Low-resolution Image Processing

• Main Authors: Chun-Yuan Yang, 楊俊元
• Other Authors: Ching-Yi Chen
• Format: Others
• Language: en_US
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/77260998873793589970

碩士 === 銘傳大學 === 電腦與通訊工程學系碩士班 === 103 === The most difficult part of achieving a high-efficiency embedded image/video processing system is how to execute complicated digital signal processing algorithm with embedded processor especially in processing high-resolution images. The whole system becomes very slow because of large volume of the processed data and complicated algorithm; as consequence, it won’t be able to achieve real-time processing. Executing motion detection in low-resolution image was already proved to be able to reduce the loading of data manipulation and to be able to help filter out noise and fake motion. However, smoothing filter pointed out in the article will affect the quality of image. Although the LL-band signal of 2-D discrete wavelet transform (DWT) domain can retain the main part of energy and information of the original image, the complex of algorithm is more suitable to the application of low-pass filter. symmetric mask-based DWT (SMDWT) has the advantage of reduced complexity, regular signal coding, short critical path, and independent sub-band codding processing. In this paper, we use PSO-based approach to automatically evolve the multiplierless 2-D SMDWT filters hardware architecture. The architecture employs only shift-and-addition operations to replace the complex floating-point multiplication and division operations. It can use shift-and-add based SMDWT filter to decompose a low-resolution image and do real-time video processing system design with low-resolution image processing technique.