In the field of computer‐aided recognition, edge feature is one of the key factors to determine recognition performance. Comparing to an optical image, since sonar image via acoustic wave is easily influenced by underwater environments such as particle density, temperature, and current, edge information should be boosted. Some image preprocessing techniques based on transform domain such as wavelet and curvelet may be good candidates but conventional methods show not only the possibility of enhancing edge features but also the limitation due to the absence of consideration to the edge direction. This study proposes an improved edge enhancement method based on curvelet transform (CVT), which is able to find out edge direction. The proposed method (PM) calculates the maximum value by ridgelet coefficients on each angular line, derived from the sub‐step of the CVT, and the real edge direction is determined by local maxima selection after finding the azimuth of this value. In addition, selective sharpening is performed according to the feature information of edge. Experimental results have shown that the PM is comparable with conventional methods in terms of edge intensity, recognition rate, and peak signal‐to‐noise ratio.

In this paper, a new fast encoding algorithm based on an efficient motion estimation (ME) process is proposed to accelerate the encoding speed of the scalable video coding standard. Through analysis of the ME process performed in the enhancement layer, we discovered that there are redundant MEs and some MEs can simply be unified at the fully overlapped search range (FOSR). In order to make the unified ME more efficient, we theoretically derive a skip criterion to determine whether the computation of rate-distortion cost can be omitted. In the proposed algorithm, the unnecessary MEs are removed and a unified ME with the skip criterion is applied in the FOSR. Simulation results show that the proposed algorithm achieves computational savings of approximately 46% without coding performance degradation when compared with the original SVC encoder.

The macroblock (MB)-based adaptive interpolation filter method has been considered to be able to achieve high coding efficiency in H.264/AVC. Although the conventional cost functions have showed a good performance in terms of rate and distortion, it still leaves room for improvement. To improve coding efficiency, we introduce a new cost function which considers two bit rates, motion vector and prediction error, and reconstruction error of MB. The filter which minimizes the proposed cost function is adaptively selected per MB. Experimental results show that the adaptive interpolation filter with the proposed cost function significantly improves the coding efficiency compared to ones using conventional cost function. It leads to about a 5.19% (1 reference frame) and 5.14% (5 reference frames) bit rate reduction on average compared to H.264/AVC, respectively.