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Research of ROI image compresssion based on visual attention model

机译:基于视觉注意力模型的ROI图像压缩研究

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Region of interest (ROI) coding is important in applications where certain parts of an image are of a higher importance than the rest of the image. Human vision system actively seeks interesting regions in images to reduce the search export in tasks, such as object detection and recognition. Similarly, prominent actions in video sequences are more likely to attract human's first sight than their surrounding neighbors. Based on the mechanism of HVS, this paper proposes a model of the focus of attention for detecting the attended regions in video sequences. It uses the similarity between the adjacent frames, establishes the gray histogram, selects the maximum similarity as predicable model, and gets position of the focus of attention in the next fame. And on the application of an algorithm for visual attention the paper shows the region of interest (ROI) coding in JPEG 2000. JPEG 2000 ROI coding is used in combination with an algorithm for VA to provide a progressive bit-stream where the regions highlighted by the VA algorithm are coded as an ROI and presented first in the bit-stream. It can be seen that there is an improvement in image quality centered on the ROI although this is achieved at the expense of reduced quality in the background of the image.
机译:感兴趣区域(ROI)编码在图像某些部分比其余部分具有更高重要性的应用中很重要。人类视觉系统会主动在图像中寻找感兴趣的区域,以减少诸如对象检测和识别之类的任务中的搜索输出。同样,视频序列中的突出动作比周围的邻居更容易吸引人的一见钟情。基于HVS机制,提出了一种视频序列中关注区域的检测关注点模型。它使用相邻帧之间的相似度,建立灰色直方图,选择最大相似度作为可预测模型,并在下一个成名中获得关注焦点的位置。并且在视觉注意力算法的应用上,本文显示了JPEG 2000中的感兴趣区域(ROI)编码。JPEG 2000 ROI编码与VA算法结合使用,以提供渐进的比特流,其中区域以高亮显示。 VA算法被编码为ROI,并首先出现在比特流中。可以看出,以ROI为中心的图像质量有所提高,尽管这是以降低图像背景质量为代价的。

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