One-bit transform (1BT)-and two-bit transform (2BT)-based block motion estimation (ME) schemes have been proposed in the literature to reduce the computational complexity of the ME process by enabling simple Boolean EX-OR matching of lower bit depth representations of image frames. Recently a multiplication-free 1BT (MF-1BT) has been proposed to facilitate 1BT to be carried out with integer arithmetic using addition and shifts only. Thresholding schemes are typically used in order to construct the lower bit depth representations utilized in 1BT and 2BT. In our experience we have observed that one problem with such schemes is that pixel values that lie on directly opposite sides of the threshold are categorized into separate classes and are, therefore, counted as a nonmatch in the search process even if they are close in value. A constrained 1BT (C-1BT) that restricts pixels with values adjacent to the transform threshold during 1BT matching, counting them as a match regardless of their 1BT value, is proposed in this paper. It is shown that the proposed C-1BT approach improves the ME accuracy of 1BT-based ME and even outperforms 2BT-based ME at macroblock level.Index Terms-Image/video coding and transmission, motion estimation (ME), one-bit transform (1BT), two-bit transform (2BT).

No abstract

In this paper, we present efficient hardware implementation of multiplication free one-bit transform (MF1BT) based and constraint one-bit transform (C-1BT) based motion estimation (ME) algorithms, in order to provide low bit-depth representation based full search block ME hardware for real-time video encoding. We used a source pixel based linear array (SPBLA) hardware architecture for low bit depth ME for the first time in the literature. The proposed SPBLA based implementation results in a genuine data flow scheme which significantly reduces the number of data reads from the current block memory, which in turn reduces the power consumption by at least 50% compared to conventional 1BT based ME hardware architecture presented in the literature. Because of the binary nature of low bit-depth ME algorithms, their hardware architectures are more efficient than existing 8 bits/pixel representation based ME architectures.Index Terms-Low bit-depth motion estimation, motion estimation hardware, source pixel based linear arrays.

In this work, a high dynamic range (HDR) image generation method using a single input image is presented. The proposed approach generates over-and under-exposed images by making use of a novel adaptive histogram separation scheme. Thus, it becomes possible to eliminate ghosting effects which generally occur when several input image containing camera/object motion are utilized in HDR imaging. Additionally, it is proposed to utilize a fuzzy logic based approach at the fusion stage which takes visibility of the inputs pixels into account. Since the proposed approach is computationally light-weight, it is possible to implement it on mobile devices such as smart phones and compact cameras. Experimental results show that the proposed approach is able to provide ghost-free and improved HDR performance compared to the existing methods 1 .

No abstract