Constrained One-Bit Transform for Low Complexity Block Motion Estimation

Abstract

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).

Modified one-bit transform method with dynamic search range

“…The 2BT and C1BT methods are also based on 1-bit operations although they use slightly different NNMP measures. 2,3 Although the 1BT, 2BT, and C1BT methods are all low-complexity solutions, they lead to relatively very low PSNR values when compared with the FS method.…”

“…Thus, many low-complexity motion estimation algorithms have been proposed, including the one-bit transform (1BT), two-bit transform (2BT), and constrained 1BT (C1BT) methods. [1][2][3] These low-complexity methods greatly reduce the complexity, but they lead to very low peak signalto-noise ratio (PSNR) values. In order to solve this problem, many hybrid methods have been proposed that combine the low-complexity methods with the FS method.…”

An Efficient Hyperspectral Image Retrieval Method: Deep Spectral-Spatial Feature Extraction with DCGAN and Dimensionality Reduction Using t-SNE-Based NM Hashing

“…(3) The first three well-structured bands are selected as principal bands instead of the full bands by comparing the value of A(l) [32][33][34].…”

A Survey on Motion Estimation Techniques

“…This damages the effectiveness of the MSE matching score, which essentially integrates the squared error contributions from all frequency components. 1-bit and 2-bit transforms have been proposed before, to improve the computational efficiency of the motion estimation step in video compression application [14] [15]. [16] describes a 2-bit transform for increasing the robustness of motion estimation (registration) in a multi frame enhancement application, this transform is most similar to the one proposed here [17].…”