摘要:
An image denoising method includes the steps of: sequentially selecting a pixel in an image as a current pixel; dynamically determining a current search block and a strength parameter; pre-denoising the comparison block of each pixel in the current search block; comparing the comparison block of the pre-denoised neighborhood pixel and the comparison block of the pre-denoised current pixel to obtain a similarity between each neighborhood pixel and the current pixel in the current search block; determining a weighting of each neighborhood pixel related to the current pixel according to the strength parameter, and a distance and the similarity between each neighborhood pixel and the current pixel in the current search block; and weighted averaging each neighborhood pixel and the current pixel in the current search block according to the weighting to obtain a reconstruction value of the current pixel.
摘要:
An image denoising method includes the steps of: sequentially selecting a pixel in an image as a current pixel; dynamically determining a current search block and a strength parameter; pre-denoising the comparison block of each pixel in the current search block; comparing the comparison block of the pre-denoised neighborhood pixel and the comparison block of the pre-denoised current pixel to obtain a similarity between each neighborhood pixel and the current pixel in the current search block; determining a weighting of each neighborhood pixel related to the current pixel according to the strength parameter, and a distance and the similarity between each neighborhood pixel and the current pixel in the current search block; and weighted averaging each neighborhood pixel and the current pixel in the current search block according to the weighting to obtain a reconstruction value of the current pixel.
摘要:
An image denoising method according to the present invention includes the steps of: sequentially selecting a pixel in an image as a current pixel; dynamically determining a current search block and a strength parameter; transferring the comparison block of each pixel in the current search block to a frequency domain; determining a current frequency basis; obtaining a similarity between each neighborhood pixel and the current pixel in the current search block according to the current frequency basis; determining a weighting of each neighborhood pixel related to the current pixel according to the strength parameter, and a distance and the current pixel in the current search block; and weighted averaging each neighborhood pixel and the current pixel in the current search block according to the weighting so as to obtain a reconstruction value of the current pixel.
摘要:
An image sensor includes a sensor matrix including a plurality of sensing elements and a plurality of shutter control lines. Each sensing element includes an electronic shutter and a photo-detector, wherein the electronic shutter controls the exposure time of the photo-detector. Each shutter control line couples to a row or column of the electronic shutters, whereby different rows or columns of the electronic shutters can be independently controlled, and the photo-detectors in the same row or column can have the same exposure time.
摘要:
A human face detection device includes a photosensitive element, a human face detection unit, and a skin color threshold generation unit. The photosensitive element is used for capturing a first image containing a first human face block. The human face detection unit compares the first image with at least one human face feature, so as to detect the first human face block. The skin color threshold generation unit is used for updating a skin color threshold value according to the detected first human face block. The skin color threshold value is used for filtering the first image signal to obtain a candidate region, the human face detection unit compares the candidate region with the at least one human face feature to obtain the first human face block, and the skin color threshold value determines whether the first human face block detected by the human face detection unit is correct.
摘要:
A shooting parameter adjustment method for face detection includes (A) acquiring an image; (B) dividing the image into a plurality of blocks, and calculating a brightness value of each of the blocks; (C) selecting at least one of the plurality of blocks, and adjusting a shooting parameter according to the brightness value of the selected block; and (D) acquiring another image according to the shooting parameter, and performing a face detection procedure with the another image. The shooting parameter adjustment method can automatically adjust a shooting parameter of an image capturing device according to brightness of different blocks in an image. Therefore, by using this method, the brightness of a face, no matter being too high or too low, can be adjusted to a value suitable for face detection, so as to improve the accuracy of the face detection procedure.
摘要:
A dynamic image compression method for human face detection includes the following steps. An original image is acquired. The image is divided into a plurality of blocks. A first brightness and a plurality of gradient values of each block are calculated. A second brightness of each block is calculated according to a brightness transformation function and the first brightness. A reconstruction image is generated according to the second brightness and the plurality of gradient values of each block. Human face detection is performed according to the reconstruction image. Therefore, gradient values within an original square are. When the human face detection process is performed through gradient direction information, a success rate of detection is greatly increased.