46 results about "Cone cell" patented technology

The present invention provides reagents and methods for modulating cone photoreceptor activity, and devices for assessment of cone photoreceptor activity.

The invention provides a human visual perception simulation-based self-adaptive low-illumination image enhancement method. The method is put forwards based on characteristics of low brightness and low contrast of a low-illumination color image and through researching an automatic adjustment process of pupils and photoreceptor cells for an environment. The method includes the following steps that: the adjustment process of the pupils for light is simulated, and the total brightness level of the image is improved; and the self-adaptive adjustment and control ability of eye vision for a low-illumination environment is simulated, and a nonlinear mapping model is designed to simulate the adjustment process of rod cells and cone cells, so that a bright and dark self-adaptation function can be obtained, and a bright and dark information fusing function is determined according to illumination distribution, and global self-adaptive adjustment is performed on brightness components; and the local contrast of the enhanced brightness image will be decreased, so that local self-adaptive contrast enforcement is performed on the image through adopting an exponential function; and finally, and color restoration is performed on the enhanced image. With the human visual perception simulation-based self-adaptive low-illumination image enhancement method of the invention adopted, the brightness, local contrast and detail information of the low-illumination color image can be effectively improved, and especially, the method has obvious effects in dark area and highlight area enhancement.

The invention relates to a cone-cell density calculation method based on image identification. The method mainly solves the prior problem that density counting of cone cells is performed manually and an eye-ground adaptive confocal laser scanning ophthalmoscope is used to obtain a visual cone-cell image and after the response frequency of the cone cells is determined, low-pass filtering is used for denoising processing so as to establish a two-valued sequence. A local maximum value corresponding to a non-zero area is searched for so that the central position of the cone cells is found. After automatic identification of the visual cone cells in the image is completed, the number of the cone cells in the image is obtained with the assistance of manual correction and finally the density counting of the cone cells is achieved. When the function which adopts a computer to counting automatically is compared with a manual counting method, the automatic calculation method is accurate, high in statistical speed, high in automation degree, checkable in analysis result and improved in detection efficiency. At the same time, a manual correction function is added so that on the basis of software analysis, error identification can be removed manually and missed cone cells can be added and thus caused result deviation is prevented.