The Remote-sensing Image Fusion Based on Gpu

Along with computing capability of the Graphic Processing Unit (GPU) getting more powerful, GPU is widely applied to the general purpose computing not just restrict to graph manipulation. Remote sensing image data can be parallel processed in many of the image fusion arithmetic. The fusion arithmetic in spatial domain is mapped to the SIMD computing way on GPU. This paper realized the product fusion, ratio fusion, high-pass filtering fusion and weighted fusion using GLSL in spatial domain, and accelerated the speed of fusion computing using RTT (Render to Texture) technology. This paper focused on the arithmetic in transformed domain, realized IHS transform fusion and DWT (Discrete Wavelet Transform) fusion. The IHS forward transform and inverse transform are mapped to two fragment shading processes, parallel computing and outputting of the 3 component in both transform processes is realized using MRT (Multiple Render Targets) technology. 2D DWT is divided into two steps of 1D DWT. An indirect address texture is created for every transform step and the transform of each level is based on the result stored on the texture of the last level. A FBO is set for every image to be fused to restore intermediate data and to do data exchange. The result shows that for the same fusion algorithm, the fusion images are identical using the two different methods, but the processing velocity in GPU implementation is obviously faster than the CPU implementation, and with the fusion algorithm getting more complicated, the fusion images getting bigger, the advantage of the velocity is more obvious in GPU implementation. * Corresponding author.