Digital image processing (DIP) is an ever growing area with a variety of applications including medicine, video surveillance, and many more. In order to improve the performance of DIP systems image processing algorithms are implemented in hardware instead of software. The idea here is mainly to obtain a system faster than software image processing. Image processing tasks such as filtering, stereo correspondence and feature detection are inherently highly parallelizable. Thus FPGAs (Field Programmable Gate Arrays) can be a useful approach in the area of Digital Signal Processing. FPGAs provide advantage of the parallelism, low cost, and low power consumption. They are semiconductor devices that contain a number of logic blocks, which can be programmed to perform anything from basic digital gate level techniques, to complex image processing
algorithms. This paper provides an overview of the various works that demonstrate the benefits of using FPGAs to implement image
processing algorithms like median filter, morphological, convolution, smoothing operation and edge detection, etc. Gray-level images are
very common in image processing. These types of images use eight bits to code each pixel value, which results in 256 different possible
shades of grey, ranging from 0 (black value) to 255 (white value). Latest generations FPGAs compute more than 160 billion multiplication and accumulation (MAC) operations per second.