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696 results about "Image evaluation" patented technology

Apparatus and method for measuring dynamic target modulation transfer function

The invention relates to a dynamic object modulation transfer function measuring method and a device thereof, pertaining to the optical property measurement field. The invention aims at providing a dynamic object modulation transfer function measuring method and a device thereof which can carry out the dynamic object modulation transfer function measurement under different fields of view, namely, uniform linear motion, uniformly-accelerated rectilinear motion, simple harmonic motion, but also can measure static target modulation transfer function and separate the static target modulation transfer function from whole machine modulation transfer function. The device consists of a light source, a collimating lens, a pupil coupling system and an electro-optical imaging system which are arranged along the ray propagation direction in sequence; the electro-optical imaging system carries out imaging towards the light source moving along the guide rail direction and line spread function is obtained from the image and carried out one-dimensional Fourier transformation so as to obtain the dynamic object modulation transfer function. The method and the device of the invention are not only suitable for static image evaluation field but also for the image evaluation field of dynamic object imaging by a time-delay electro-optical imaging system.
Owner:江苏亚星波纹管有限公司

Robust mechanism research method of characteristic significance in image quality evaluation

The invention discloses a robust mechanism research method of characteristic significance in image quality evaluation. The robust mechanism research method comprises the following steps: firstly, determining a target function of characteristic selection in the image quality evaluation, and initializing a model parameter; secondly, adding an optimal characteristic into a characteristic matrix, and removing a characteristic disturbance term; thirdly, calculating the significance of the characteristic selection in an image quality evaluation system; fourthly, judging whether the significance meets a system robust requirement or achieves an upper limit of a characteristic number; and finally, verifying a model classification effect. The characteristic significance is measured through an imported system characteristic signal to noise ratio, a constrained optimization problem of a smooth convex function in the image quality evaluation system is solved, interference on a classification face by non-significant characteristics is effectively lowered, the robustness of the image evaluation system is improved, and the self-adaptive optimization problem of characteristic attribute selection on the basis of an image quality evaluation network of a learning mechanism is solved.
Owner:SOUTH CHINA AGRI UNIV
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