Image processing device, imaging device, and image processing method
An image processing device and image processing technology, which are applied in the directions of image data processing, image data processing, image enhancement, etc., can solve the problems of depth data accuracy decline, achieve the effect of reducing processing load and suppressing the decline of accuracy
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Embodiment approach 1
[0061] figure 1 It is a block diagram showing the functional configuration of the image processing device 10 according to the first embodiment. The image processing device 10 generates depth data of the first image by using the first image and the second image (for example, stereoscopic image) captured from different viewpoints. The first image and the second image are, for example, stereoscopic images (images for the left eye and images for the right eye).
[0062] Such as figure 1 As shown, the image processing device 10 according to this embodiment includes a parallax value calculation unit 11 , a segmentation unit 12 , and a depth data generation unit 13 .
[0063] The parallax value calculation unit 11 detects a corresponding pixel in the second image for each representative pixel in the first image, thereby calculating a parallax value between the representative pixel and the corresponding pixel. That is, the parallax value calculation unit 11 calculates a parallax va...
Embodiment approach 2
[0083] Next, Embodiment 2 will be described with reference to the drawings.
[0084] Figure 4 It is a block diagram showing the functional configuration of the image processing device 20 according to the second embodiment. The image processing device 20 according to the present embodiment includes a feature point calculation unit 21, an alignment processing unit 22, a parallax value calculation unit 23, a segmentation unit 24, a segment combination unit 25, a depth data generation unit 26, and an image processing unit. 27.
[0085]The feature point calculation unit 21 calculates feature points of the first image as representative pixels. Specifically, the feature point calculating section 21 calculates feature points using the feature quantities extracted by the feature quantity extraction method. As a feature quantity extraction method, for example, reference 1 (David G. Lowe, "Distinctive image features from scale-invariant key points", International Journal of Computer ...
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