Analysis And Comparison Of Image Salient Region Extraction Algorithms Based On Attention Mechanism

In the late 1980s, Analysis of Image saliency feature based on biological perception were beginning to emerge, and were gradually becoming the focus of biological perception research. This method combines with the theory of human psychology and physiology knowledge, based on human visual attention mechanism to simulate human eye functions to build a saliency extraction model. As an independent technology, extracting visual saliency feature could help us analyze and understand digital image better. Research on image saliency extracting is an integrated process of image analysis, feature extracting and human visual feature discovering, and it is important to kinds of applications based on image analysis and understanding. This topic is to analyze kinds of saliency map generation models, implement saliency map generation algorithms based on visual attention, develop algorithms implementation and comparison system, and analyze the results.This topic introduces five saliency map generation models. Itti model is a typical spatial-based attention model. This model extracts various features from one image including color, illumination and orientation, then generates attention maps on each feature dimension, finally, fuses these attention maps into saliency map; SMG(Saliency map generation) algorithm is the "center-surrounding contrast in scale, interpolation fusion between scales" feature-based attention model; HC(Histogram-based Contrast) algorithm defines saliency values for image pixels using color statistics of the input image; RC(Region-based Contrast) algorithm integrates spatial relationships into region-level contrast computation, it needs to cut the image into segments, and then computes the saliency value based on color histogram on region level; FT(Frequency-tuned) is the algorithm based on Frequency-tuned salient region detection adding edge detection.Based on the above research work, I make a pectination to the theory of saliency feature extraction based on visual attention. Re-implement the Itti algorithm and the SMG algorithm. Then I compare the algorithms with the precision of salient region extracting. Microsoft Research Asia (MSRA) provides a significant object image library as the reference standard. So, RC algorithm has the highest precision, but this method's storage and computation is large; SMG algorithm is efficient, and the overhead is low, this helps SMG meet the requirement of real-time of image retrieval; Itti algorithm needs to down-sampling to the original image, so the saliency map has only the scale of 1/256 of original image; FT algorithm has high efficiency, and the saliency map is full resolution; LC algorithm avoids image segmentation, so it is effectual to the image difficult to automatic segmentation.