New Edge-Directed Interpolation Based-Lifting DWT and MSPIHT Algorithm for Image Compression

The amount of image data generated in multimedia applications is ever increasing. The image compression plays vital role in multimedia applications. The ultimate aim of image compression is to reduce storage space without degrading image quality. Compression is required whenever the data handled is huge they may be required to sent or transmitted and also stored. The New Edge Directed Interpolation (NEDI)-based lifting Discrete Wavelet Transfrom (DWT) scheme with modified Set Partitioning In Hierarchical Trees (MSPIHT) algorithm is proposed in this paper. The NEDI algorithm gives good visual quality image particularly at edges. The main objective of this paper is to be preserving the edges while performing image compression which is a challenging task. The NEDI with lifting DWT has achieved 99.18% energy level in the low frequency ranges which has 1.07% higher than 5/3 Wavelet decomposition and 0.94% higher than traditional DWT. To implement this NEDI with Lifting DWT along with MSPIHT algorithm which gives higher Peak Signal to Noise Ratio (PSNR) value and minimum Mean Square Error (MSE) and hence better image quality. The experimental results proved that the proposed method gives better PSNR value (39.40 dB for rate 0.9 bpp without arithmetic coding) and minimum MSE value is 7.4.

Efficient video downscaling transcoder from MPEG-2 to H.264

The new H.264 video coding standard achieves significantly higher compression performance than MPEG-2. As the MPEG-2 is popular in digital TV, DVD, etc., bandwidth or memory space can be saved by transcoding those streams into H.264 in these applications. Unfortunately, the huge complexity keeps transcoding from being widely used in practical applications. This paper proposes an efficient transcoding architecture with a smart downscaling decoder and a fast mode decision algorithm. Using the proposed architecture, huge buffering memory space is saved and the transcoding complexity is reduced. Performance of the proposed fast mode decision algorithm is validated by experiments.

CONVERGENCE ANALYSIS AND MRALLEL IMPLEMENTION FOR THE DIRECTEDGRAPH -ALGORITHM

In this paper we discuss the convergence of the directed graph-algorithm for solving a kind of optimization problems where the objective and subjective functions are all separable, and the parallel implementation process for the directed graph -algorithm is introduced.

Dominant edge direction based fast intra mode decision in the H.264/AVC encoder

The H.264/AVC video coding standard uses an intra prediction mode with 4×4 and 16×16 blocks for luma and 8×8 blocks for chroma. This standard uses the rate distortion optimization (RDO) method to determine the best coding mode based on the compression performance and video quality. This method offers a large improvement in coding efficiency compared to other compression standards, but the computational complexity is greater due to the various intra prediction modes. This paper proposes a fast intra mode decision algorithm for real-time encoding of H.264/AVC based on the dominant edge direction (DED). The DED is extracted using pixel value summation and subtraction in the horizontal and vertical directions. By using the DED, three modes instead of nine are chosen for RDO calculation to decide on the best mode in the 4×4 luma block. For the 16×16 luma and the 8×8 chroma, only two modes are chosen instead of four. Experimental results show that the entire encoding time saving of the proposed algorithm is about 67% compared to the full intra search method with negligible loss of quality.

Directional Edge Boxes： Exploiting Inner Normal Direction Cues forEffective Obiect Prooosal Generation

Edges are important cues for localizing object proposals. The recent progresses to this problem are mostly driven by defining effective objectness measures based on edge cues. In this paper, we develop a new representation named directional edges on which each edge pixel is assigned with a direction toward object center, through learning a direction prediction model with convolutional neural networks in a holistic manner. Based on directional edges, two new objectness measures are designed for ranking object proposals. Experiments show that the proposed method achieves 97.1% object recall at an overlap threshold of 0.5 and 81.9% object recall at an overlap threshold of 0.7 at 1 000 proposals on the PASCAL VOC 2007 test dataset, which is superior to the state-of-the-art methods.

Direct wave and edge waves radiated into a solid medium by a circular thickness-mode transducer

The transient acoustic field radiated by a piezoelectric thickness-mode transducer into a solid medium is theoretically analysed. It is proved that the field consists of the direct wave, the longitudinal edge waves, the shear edge.waves, the head wave and the surface waves. The wavefront approximations of all these waves are given which result in a clear physical picture which is not only simple but also cotains the main features of the field. The theoretical result well describes the experiment.