Depth map super-resolution processing method

    公开(公告)号:US10115182B2

    公开(公告)日:2018-10-30

    申请号:US15216332

    申请日:2016-07-21

    Abstract: The present invention discloses a depth map super-resolution processing method, including: firstly, respectively acquiring a first original image (S1) and a second original image (S2) and a low resolution depth map (d) of the first original image (S1); secondly, 1) dividing the low resolution depth map (d) into multiple depth image blocks; 2) respectively performing the following processing on the depth image blocks obtained in step 1); 21) performing super-resolution processing on a current block with multiple super-resolution processing methods, to obtain multiple high resolution depth image blocks; 22) obtaining new synthesized image blocks by using an image synthesis technology; 23) upon matching and judgment, determining an ultimate high resolution depth image block; and 3) integrating the high resolution depth image blocks of the depth image blocks into one image according to positions of the depth image blocks in the low resolution depth map (d). Through the depth map super-resolution processing method of the present invention, depth information of the obtained high resolution depth maps is more accurate.

    Distance estimation method based on handheld light field camera

    公开(公告)号:US10482617B2

    公开(公告)日:2019-11-19

    申请号:US16212344

    申请日:2018-12-06

    Abstract: A distance estimation method based on a handheld light field camera is disclosed and includes: S1: extracting parameters of the light field camera; S2: setting a reference plane and a calibration point; S3: refocusing a collected light field image on the reference plane, to obtain a distance between a main lens and a microlens array of the light field camera, and recording an imaging diameter of the calibration point on the refocused image; and S4: inputting the parameters of the light field camera, the distance between the main lens and the microlens array, and the imaging diameter of the calibration point on the refocused image to a light propagation mathematical model, and outputting a distance of the calibration point. The present application has high efficiency and relatively high accuracy.

    Depth estimation method based on light-field data distribution

    公开(公告)号:US10346997B2

    公开(公告)日:2019-07-09

    申请号:US15809769

    申请日:2017-11-10

    Abstract: A depth estimation method based on light-field data distribution includes the following steps: S1. adjusting pixel distribution of input light-field images to generate a series of refocused light-field images having different focal lengths; S2. for a spatial point, corresponding to a macro-pixel, extracting intensity ranges for the macro-pixel from the refocused light-field images, and then selecting one refocused light-field image corresponding to a minimum intensity range, the focal length of the selected refocused light-field image being taken as a scene depth of the macro-pixel; the macro-pixel corresponding to one point in an actual scene, the intensity range of the macro-pixel being a variation range of intensity values of all points within the macro-pixel; and repeating the step S2 to obtain scene depths of all macro-pixels.

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