Image quality evaluation method, electronic equipment and storage medium

Abstract

The embodiment of the invention relates to the field of image processing, and discloses an image quality evaluation method, electronic equipment and a storage medium. The method comprises the following steps: carrying out foreground identification on a speckle pattern to obtain a foreground region of the speckle pattern; counting the ratio of hole pixel points in a region corresponding to the foreground region in a depth map corresponding to the speckle pattern; and evaluating the quality of the depth map according to the proportion. According to the scheme, when the quality evaluation is performed on the depth map based on the voidage, only the voidage corresponding to the foreground object is counted, so that the voidage statistics is more reliable and robust, and the quality evaluation of the depth is reflected more truly.

Description

technical field [0001] The embodiments of the present application relate to the field of image processing, and in particular, to an image quality evaluation method, an electronic device, and a storage medium. Background technique [0002] Structured light camera is a camera that obtains depth data by emitting an active infrared light source. It is widely used in the field of 3D face recognition, and is used in a wide range of scenarios, such as payment scenarios, door lock scenarios and rail crossing scenarios. In these scenarios , the average person is the subject of the image, and other backgrounds are empty, even beyond the working distance of the camera itself. To evaluate the quality of the depth map or whether the camera structure is deformed, an important indicator is the void rate of the depth map. The conventional void rate statistical method: the denominator is the total number of pixels in the depth map, and the numerator is the depth value of the depth map. 0 fo...

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Problems solved by technology

[0003] However, in actual use, when the speckle image used to generate the depth image has a lot of background, the depth restoration algorithm cannot restore a high-quality depth image, resulting in an increase in the number of pixels with a depth value of 0 in the depth image. , the error of the calculated void rate increases, and it is impossible to truly evaluate the quality of the depth map, which will cause misjudgment of the business

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