Rapidly obtaining accurate dense disparity maps has been the focus of stereo matching research. At present, approaches that achieve superior require a large amount computation, which is not suitable for practical applications. To address this issue, paper proposes an efficient local method based on adaptive exponentially weighted moving average filter and simple linear iterative clustering segm...

Efficient and accurate segmentation of sea ice floes from high-resolution optical (HRO) remote sensing images is crucial for understanding evolutions climate changes, especially in coping with the large data volume. Existing methods suffer noise interference mixture water caused high error less robustness. In this article, we propose a novel floe algorithm HRO based on texture-sensitive superpi...

We show how pixel-based methods can be applied to a sparse image representation resulting from a superpixel segmentation. On this sparse image representation we only estimate a single motion vector per superpixel, without working on the full-resolution image. This allows the accelerated processing of high-resolution content with existing methods. The use of superpixels in optical flow estimatio...

To solve the problems of image threshold segmentation based on weak continuous constraint theory, running time is long, and two parameters need to be selected manually, therefore a fast single-parameter energy function thresholding for region information (FSEFTISRI) proposed in this paper. The FSEFTISRI algorithm uses simple linear iterative clustering (SLIC) technology pre-block image, extract...

Salient object detection is a long-standing problem in computer vision and plays a critical role in understanding the mechanism of human visual attention. In applications that require object-level prior (e.g. image retargeting), it is desirable that saliency detection highlights holistic objects. Lately over-segmentation techniques such as SLIC superpixel [6], Meanshift [1], and graph-based [3]...