Integral image based binarization for low-complexity motion estimation

Today, high resolution video applications are demanded with the use of high resolution televisions, cameras, smart phones. the requirement for low processing load video coding methods increase due to constraints such as power consumption and limited memory in these devices. in video coding standards, most of the processing load still originates from the motion estimation part. in this study, a low bit-depth representation based motion estimation method that has low computational load is proposed. in this approach, video frames are binarized efficiently by using integral image and the representation of video frames in terms of two bits is performed. matching operation is carried out on these binary image frames using hardware-friendly ex-or operation instead of conventional sad (sum of absolute difference this study is the first attempt of using the integral image for the binarization process in the motion estimation. while the proposed method improves the motion estimation accuracy compared to the 1bt based approaches available in the literature, it provides similar motion estimation performance with the two-bit depth based approaches. additionally, it reduces the processing load of these methods, especially during the binarization phase.