Image fusion quality detection method and device
A quality inspection method and image fusion technology, applied in the field of image processing, can solve problems such as the failure to track people and the inability to accurately understand the situation of the person being photographed, and achieve a good positioning effect
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[0042] Example one
[0043] The first embodiment of the application provides an image fusion quality detection method, such as figure 1 Shown, including:
[0044] Step 110: Search for an image frame of the tracked person from each frame of the video image;
[0045] Since the embodiments of the present application have high real-time requirements for the tracked person, a deep convolutional neural network model with fast calculation speed is used for image judgment;
[0046] Among them, the search for the image frame of the tracked person from each frame of the video image is specifically: building a deep convolutional neural network model, starting from the input layer, and sequentially passing through convolution C 1 Layer (output image size [256,256,8]), depth convolutional layer D 1 (Output image size [128,128,16]), convolutional layer C 2 (Output image size [64,64,32]), depth convolutional layer D 2 (Output image size [32,32,64]), convolutional layer C 3 (Output image size [16,16,1...
Example Embodiment
[0082] Example two
[0083] The second embodiment of the application provides an image fusion quality detection device, such as Figure 5 Shown, including:
[0084] The tracked person image search module 510 is used to search for the tracked person's image frame from each frame of the video image;
[0085] The image fusion module 520 is used to perform image fusion on multiple tracked images according to the wavelet transform image fusion method, the contour wavelet fusion method, and the scale-invariant feature transform image fusion method;
[0086] The standard deviation-based fusion image quality detection module 530 is configured to calculate standard deviations according to the fusion results, and determine the image fusion quality according to the standard deviations.
[0087] Wherein, the tracked person image search module 510 is specifically used to construct a deep convolutional neural network model; starting from the input layer, it sequentially passes through the first conv...
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