Nowadays, the wavelet transforms can be used in many applications such as image compression, video compression and data compression. JPEG 2000 is a wavelet-based image compression standard. It is widely used in many areas of the image. This is because it is a lossless compression and easy to implement. Implementation wavelet transforms using FPGA is to make designer easily to process the image. This is because FPGA like a simulator so the designer can modify the implementation easily. Wavelet transforms have been used for compact signal and image, de-noising, resize image size and edge detection image. Numerous research works have proven that space-frequency and space-scale expansions with this family of analysis functions provided a very efficient framework for signal or image data. Wavelet transform has many advantages. For example, it can capture transient behavior of a time-domain signal or spatial activities, conventional transform techniques, such as the Fourier Transform are not adequate. Wavelet transforms‟ basic function has varying width instead of the fixed width. The varying width makes the wavelet transform a powerful tool for signal analysis in general and image processing in particular. The wavelet transform itself offers great design flexibility. This work presents a system using FPGA for de-noise, resize image, and edge detection on image. The discrete wavelet transform based on Le Gall wavelet is used in implementation in this work. VHDL Language is used to write program to implement the Le Gall algorithm. Finally, the result from Matlab is compared with the result from the Modelsim to confirm that the both result are same. If both results show the same, then the implementation of the VHDL language is true.
Implementation wavelet transform in fpga Lau Chee Leong_E3_2007_875000062_NI