Image Interpolation with Edges Preserving and Implementation on the Real ADAS Platform

To save transmission, processing and memory resources in Advanced Driver Assistance Systems (ADAS), it is often necessary to reduce the image resolution. Sometimes it is necessary to increase it after the transmission. Both resolution changes involve an image interpolation process. This paper describes implementation for three well-known interpolation methods, nearest neighbour interpolation (NN), bilinear interpolation (BL) and bicubic interpolation (BC), on a real automotive AMV ALPHA platform, using multiple processors on the same System on Chip (SoC). Implementation was done using C programming language and Vision Software Development Kit (VSDK). Specific attention is given to the optimal distribution of tasks to the certain processor. The results have shown that, on the real automotive AMV ALPHA platform, BL interpolation achieves the best trade-off between the quality of interpolated image for the usage in automotive image-processing based algorithms and execution time, especially for the algorithms where the lower frame rate is acceptable (like surround-view, park assist, etc.).