Semi-hierarchical based motion estimation algorithm for the dirac video encoder

Having fast and efficient motion estimation is crucial in today’s advance video compression technique since it determines the compression efficiency and the complexity of a video encoder. In this paper, a method which we call semi-hierarchical motion estimation is proposed for the Dirac video encoder. By considering the fully hierarchical motion estimation only for a certain type of inter frame encoding, complexity of the motion estimation can be greatly reduced while maintaining the desirable accuracy. The experimental results show that the proposed algorithm gives two to three times reduction in terms of the number of SAD calculation compared with existing motion estimation algorithm of Dirac for the same motion estimation accuracy, compression efficiency and PSNR performance. Moreover, depending upon the complexity of the test sequence, the proposed algorithm has the ability to increase or decrease the search range in order to maintain the accuracy of the motion estimation to a certain level

Dynamically variable step search motion estimation algorithm and a dynamically reconfigurable hardware for its implementation

Motion Estimation (ME) is the most computationally intensive part of video compression and video enhancement systems. For the recently available High Definition (HD) video formats, the computational complexity of De full search (FS) ME algorithm is prohibitively high, whereas the PSNR obtained by fast search ME algorithms is low. Therefore, ill this paper, we present Dynamically Variable Step Search (DVSS) ME algorithm for Processing high definition video formats and a dynamically reconfigurable hardware efficiently implementing DVSS algorithm. The architecture for efficiently implementing DVSS algorithm. The simulation results showed that DVSS algorithm performs very close to FS algorithm by searching much fewer search locations than FS algorithm and it outperforms successful past search ME algorithms by searching more search locations than these algorithms. The proposed hardware is implemented in VHDL and is capable, of processing high definition video formats in real time. Therefore, it can be used in consumer electronics products for video compression, frame rate up-conversion and de-interlacing(1)

Low computational complexity variable block size (VBS) partitioning for motion estimation using the Walsh Hadamard transform (WHT)

Variable Block Size (VBS) based motion estimation has been adapted in state of the art video coding, such as H.264/AVC, VC-1. However, a low complexity H.264/AVC encoder cannot take advantage of VBS due to its power consumption requirements. In this paper, we present a VBS partition algorithm based on a binary motion edge map without either initial motion estimation or Rate-Distortion (R-D) optimization for selecting modes. The proposed algorithm uses the Walsh Hadamard Transform (WHT) to create a binary edge map, which provides a computational complexity cost effectiveness compared to other light segmentation methods typically used to detect the required region

Energy-efficient acceleration of MPEG-4 compression tools

We propose novel hardware accelerator architectures for the most computationally demanding algorithms of the MPEG-4 video compression standard-motion estimation, binary motion estimation (for shape coding), and the forward/inverse discrete cosine transforms (incorporating shape adaptive modes). These accelerators have been designed using general low-energy design philosophies at the algorithmic/architectural abstraction levels. The themes of these philosophies are avoiding waste and trading area/performance for power and energy gains. Each core has been synthesised targeting TSMC 0.09 μm TCBN90LP technology, and the experimental results presented in this paper show that the proposed cores improve upon the prior art

Vision-based Real-Time Aerial Object Localization and Tracking for UAV Sensing System

The paper focuses on the problem of vision-based obstacle detection and tracking for unmanned aerial vehicle navigation. A real-time object localization and tracking strategy from monocular image sequences is developed by effectively integrating the object detection and tracking into a dynamic Kalman model. At the detection stage, the object of interest is automatically detected and localized from a saliency map computed via the image background connectivity cue at each frame; at the tracking stage, a Kalman filter is employed to provide a coarse prediction of the object state, which is further refined via a local detector incorporating the saliency map and the temporal information between two consecutive frames. Compared to existing methods, the proposed approach does not require any manual initialization for tracking, runs much faster than the state-of-the-art trackers of its kind, and achieves competitive tracking performance on a large number of image sequences. Extensive experiments demonstrate the effectiveness and superior performance of the proposed approach.Comment: 8 pages, 7 figure

Adaptive Temporal Compressive Sensing for Video

This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to real-time implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems.Comment: IEEE Interonal International Conference on Image Processing (ICIP),201

Scalable video transcoding for mobile communications

Mobile multimedia contents have been introduced in the market and their demand is growing every day due to the increasing number of mobile devices and the possibility to watch them at any moment in any place. These multimedia contents are delivered over different networks that are visualized in mobile terminals with heterogeneous characteristics. To ensure a continuous high quality it is desirable that this multimedia content can be adapted on-the-fly to the transmission constraints and the characteristics of the mobile devices. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a technique to convert an H.264/AVC bitstream without scalability to a scalable bitstream with temporal scalability as part of a scalable video transcoder for mobile communications. The results show that when our technique is applied, the complexity is reduced by 98 % while maintaining coding efficiency