An Energy Efficient and High Speed Image Compression System Using Stationary Wavelet Transform

Image compression is one of the interesting domains nowadays in all areas of research. Everybody working with huge of amount of data in their daily life. In-order to deal with such huge amount of data, there is a need to store and compress the data. So there is a need to develop a system to compress and store the data. JPEG 2000 is a system to achieve this object. In this paper an area efficient and high speed JPEG2000 architecture has been developed to compress the image data. To implement JPEG2000 system, here a transform called stationary wavelet transform has been used. Stationary wavelet transform reduces the bottlenecks existing in the wavelet transform. Stationary wavelet transform avoids the problem of invariance-translation of the already existing discrete wavelet transform. The proposed stationary wavelet transform based JPEG2000 improves the speed and efficiency of power compared to the discrete wavelet transform based JPEG2000. Many image compression applications such as tele-medicine, satellite imaging, medical imaging require high-speed, low power compression techniques with small chip area. This paper has an analysis on the speed of JPEG2000 using stationary wavelet transform and it will be compared theoretically and practically with the JPEG2000 using discrete wavelet transform. The amount of information missing in the test image usually been very small when compared to the DWT based JPEG2000.The MSE and PSNR values proved to be better when compared to the DWT based JPEG2000. The proposed SWT based JPEG2000 compresses and decompresses the image at a faster rate than the DWT based JPEG2000.Finally the design will be implemented in XILINX Virtex-4 FPGA Kit. .The power consumption of the proposed method proved to be 290mW compared to other types of compression techniques

VLSI Implementation of Medical Image Fusion Using DWT-PCA Algorithms

Nowadays, the usage of DIP is more important in the medical field to identify the activities of the patients related to various diseases. Magnetic Resonance Imaging (MRI) and Computer Tomography (CT) scan images are used to perform the fusion process. In brain medical image, MRI scan is used to show the brain structural information without functional data. But, CT scan image is included the functional data with brain activity. To improve the low dose CT scan, hybrid algorithm is introduced in this paper which is implemented in FPGA. The main objective of this work is to optimize performances of the hardware. This work is implemented in FPGA. The combination of Discrete Wavelet Transform (DWT) and Principle Component Analysis (PCA) is known as hybrid algorithm. The Maximum Selection Rule (MSR) is used to select the high frequency component from DWT. These three algorithms have RTL architecture which is implemented by Verilog code. Application Specified Integrated Chips (ASIC) and Field Programmable Gate Array (FPGA) performances analyzed for the different methods. In 180 nm technology, DWT-PCA-IF architecture achieved 5.145 mm2 area, 298.25 mW power, and 124 ms delay. From the fused medical image, mean, Standard Deviation (SD), entropy, and Mutual Information (MI) performances are evaluated for DWT-PCA method