DWT-PCA Based Image Fusion Using GPU

Image fusion techniques have been widely used in areas like satellite imaging, bio-medical imaging, military purpose etc. Image fusion is classified into two group namely spatial domain fusion and transform domain fusion. When spatial domain fusion technique like Principal Component Analysis (PCA) alone is used, it might create some spatial distortion. Such distortions can be handled with the help of frequency domain approach. In the proposed method, in order to combine a multispectral image and panchromatic image of satellite, the PCA can be combined with Discrete Wavelet Transform (DWT). Daubechies wavelets (db4) are used. This is a new approach for image fusion. For parallelizing and increasing the execution speed of the proposed work, a general purpose Graphics Processor Unit (GPU) is used. Driven by the insatiable market demand for real time, high definition 3D graphics, the programmable Graphic Processor Unit or GPU has evolved into a highly parallel, multi-threaded, many core processor with tremendous computational horsepower and very high memory bandwidth. CUDA is a general purpose parallel computing platform and programming model that leverages the parallel compute engine in GPUs to solve many complex computational problems in a more efficient way than on a CPU. When the image fusion is done using GPU, it will be more efficient and it helps to partition the problem into coarse sub problems that can be solved independently in parallel by blocks of threads and each sub problems into finer pieces that can be solved cooperatively in parallel by all threads within the block. With the help of GPU the image fusion can be done faster.