In image processing, FPGAs have shown very high performance in spite of their low operational frequency. This high performance comes from (1) high parallelism in applications in image processing, (2) high ratio of 8 bit operations, and (3) a large number of internal memory banks on FPGAs which can be accessed in parallel. In the recent micro processors, it becomes possible to execute SIMD instructions on 128 bit data in one clock cycle. Furthermore, these processors support multi-cores and large cache memory which can hold all image data for each core. In this paper, we compare the performance of FPGAs with those processors using three applications in image processing; two-dimensional filters, stereo-vision and k-means clustering, and make it clear how fast is an FPGA in image processing, and how many hardware resources are required to achieve the performance.