Since Sub-pixel Morphological Anti-Aliasing (SMAA) algorithm extracts images with less contour and needs larger storage, an improved algorithm for SMAA was presented.In the improved algorithm, the multiplication of luminance of a pixel and an adjustable factor was regarded as a dynamic threshold, which was used to decide whether the pixel is a boundary pixel. Compared with fixed threshold for boundary decision in SMAA, the dynamic threshold is stricter for deciding whether a pixel is a boundary one, so the presented algorithm can extract more boundaries. Based on the analysis of different morphological models and used storage, some redundant storages were merged so as to reduce the size of memory. The algorithm was implemented by Microsoft DirectX SDK and HLSL under Windows 7. The experimental results show that the proposed algorithm can extract clearer boundaries and the size of the memory is reduced by 51.93%.

When the transcendental function is used in the calculation of the piece-wise linear approximation algorithm, the accuracy can not be determined in advance and part of interval resources are wasted. In order to solve the problems, an improved piece-wise linear approximation algorithm of transcendental function was proposed. The proposed algorithm calculated a linear approximation function with predefined interval endpoints and adjusted the function by the concave of the function to be approximated and then calculated the maximum error between the function adjusted and the function to be approximated. The approximation intervals would be adjusted automatically based on the precision requirement and a fewer number of segments would be obtained by such iterative process. The proposed algorithm was simulated in Matlab. The simulation results show that the number of segments of the proposed algorithm is reduced by 60% compared with the equal division method. Thus, the proposed algorithm can reduce the resource consumption of the Look Up Table (LUT) greatly on the premise of guaranteeing accuracy.