Adaptive bit-plane selection-based low complexity motion estimation for screen content coding

Abstract

Screen content video coding has become an emerging research topic with the spread of applications such as cloud gaming, screen/desktop virtualization, and mobile or external display interfacing. Screen content videos have different features compared to conventional camcorder-captured scenes. In this work, a novel low bit-depth representation-based motion estimation approach is proposed to exploit screen content specific features to improve coding efficiency. The proposed approach is based on an adaptive selection of Gray-coded bit-planes in order to generate low bit-depth representation of original screen content frames. The experimental results show that the motion estimation performance of the proposed approach is significantly better compared to the methods in the same category for screen content videos.

Improved Search Pattern with Discrete Wavelet Transform for Video Steganography

“…The C2BT reduces the computational complexity of concealed text frames to 2-bit representations. The results of the simulation show that the C2BT algorithm increases the accuracy of the text by 0.35 dB for 2BT-BME and 0.28 dB for C1BT-Block Motion Estimation (BME), respectively [12]. A proposed fast motion estimation with data hiding based on the enhanced forced one-bit transform has been proposed [13].…”