Abstract. This paper proposes a novel low-complexity implementation with one parameter two dimensions cubic convolution interpolation (2D-CCI) of image interpolation for spaceborne georeferencing. The experiment results demonstrate that (1) the proposed scheme can achieve better performance without increasing the computational complexity compared to the traditional CCI; (2) the number of multiplication and addition is reduced to 33.33% and 40% respectively compared with original CCI; (3) the occupied resources of LUTs, register, DSP and memory are reduced to 23.7%, 21.9%, 18.5% and 25%, respectively; (4) the speedup time of the proposed Implementation is about 25 times higher than that when using the PC-based implementation.

Abstract. This paper analyzes a varieties of procedure of remote sensing data processing, and explores the common mathematical models, common algorithm models, and public function processing units of data processing shared by different tasks or even different parts within an individual task. Public modules are established to improve the parallelism of remote sensing data processing based on FPGA, which has excellent parallel processing performance. In addition, in order to reduce the resource consumption and increase the calculation efficiency of the designed FPGA program, the method of avoiding floating-point arithmetic and division operation in FPGA programming are discussed in this paper. There are a large number of common calculation modules between different tasks, such as the rotation matrix calculation module in attitude solution, geometric correction, and orthorectification task. Image preprocessing, feature information extraction, image threshold separation, and connected region markers are all common processing modules for a target detection task. In the same task, there is also a common calculation module. When using the FPGA design program, the power series of 2 can be used to convert the floating-point operation to fixed-point operation with an acceptable precision. A similar approach can transform the division operation into multiplication and shift operations, thereby improve the computational performance of FPGA programming.