Image saliency detection method and device, storage medium and processor
A detection method and remarkable technology, applied in the field of image processing, can solve problems such as low image accuracy, and achieve the effect of solving low accuracy and improving accuracy
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Embodiment 1
[0031] An embodiment of the present invention provides an image saliency detection method.
[0032] figure 1 is a flowchart of an image saliency detection method according to an embodiment of the present invention. Such as figure 1 As shown, the method includes the following steps:
[0033] Step S102, performing superpixel segmentation on the depth map of the target image to obtain multiple superpixels of the target image.
[0034] In the technical solution provided in the above step S102 of the present application, superpixel segmentation is performed on the depth map of the target image to obtain multiple superpixels of the target image.
[0035] When the human eye is looking at a scene, it will first be attracted by the most glaring or eye-catching part of the visual scene, and this part is the most prominent area in the visual scene. The visual saliency detection in this embodiment is to let the computer simulate the work done by the human eye at this moment, that is, ...
Embodiment 2
[0078] The technical solutions of the present invention will be described below in conjunction with preferred embodiments. Specifically, a saliency detection method for a stereoscopic video is used as an example for illustration.
[0079] figure 2 is a schematic diagram of image saliency detection according to an embodiment of the present invention. Such as figure 2 As shown, for each frame of picture, the input is the color RGB image of the left viewpoint of the current frame, and the depth map (Depth) is calculated from left to right. The depth value of the depth map is a relative value, which has been normalized to 0 to 255 between. Input the RGB image and depth map of the left view point in the previous frame, and calculate the depth saliency map (Depth saliency map), motion saliency map (Motion saliency map) and two-dimensional static saliency map (2D static saliency map), and then The depth saliency map, motion saliency map and 2D static saliency map are fused usin...
Embodiment 3
[0114] image 3 is a schematic diagram of an image saliency detection device according to an embodiment of the present invention. Such as image 3 As shown, the device includes: a segmentation unit 10 , a processing unit 20 and an execution unit 30 .
[0115] The segmentation unit 10 is configured to perform superpixel segmentation on the depth map of the target image to obtain multiple superpixels of the target image.
[0116] The processing unit 20 is configured to perform clustering processing on each superpixel to obtain a first number of classes for each superpixel, wherein the cluster center of the class with the largest number of pixels in the first number of classes is each Target cluster centers for superpixels.
[0117] The execution unit 30 is configured to execute a first preset algorithm on the target cluster center of each superpixel to obtain a depth saliency map of the target image.
[0118] Optionally, the execution unit 30 includes: a first determination ...
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