Structural Similarity Index (SSIM) is a common and useful image assessment method, and is better than mean square error (MSE) and peak signal to noise ratio (PSNR). However, when evaluating the quality of blur images and noise images, the correlation coefficient between the assessment results of SSIM and the subjective ones is low. A method based on visual structural similarity (VSSIM) for image quality assessment is proposed in this paper. The method is based on the multichannel properties of the log-polar Gabor filter and contrast sensitivity function. Multi-channel visual feature of distorted and reference images with log-polar Gabor transformation is extracted, and then the value of each channel’s SSIM is calculated, and finally, all the SSIM are mixed together according to the weight calculated by the contrast sensitivity function. Experimental results show that VSSIM can assess the blur and noise image quality precisely.
The modulation transfer function (MTF) is the tool most commonly used for quantifying the performance of an electro-optical imaging system. Recently, trapezoid-shaped pixels were designed and used in a retina-like sensor in place of rectangular-shaped pixels. The MTF of a detector with a trapezoidal pixel array is determined according to its definition. Additionally, the MTFs of detectors with differently shaped pixels, but the same pixel areas, are compared. The results show that the MTF values of the trapezoidal pixel array detector are obviously larger than those of rectangular and triangular pixel array detectors at the same frequencies.
The pixels of a retina-like sensor are arranged in concentric rings, and the output image is given in log-polar coordinates. Thus, additional residual errors will not be produced when the output image is rotated. Therefore, retina-like sensors have obvious advantages and many prospects for applications in the fields of image rotation and rapid image rotation-elimination. In this study, a theory concerning the image rotation of a retina-like sensor is proposed, and a solution based on the theory is presented and realized for eliminating image rotation caused by camera rotation. The camera rotation angle is obtained using a microelectromechanical systems digital accelerometer and gyroscope; only the readout sequence of each row from static random-access memory must be changed to achieve image rotation-elimination. Several image rotation-elimination experiments have been performed which show that the proposed solution is simple, accurate, and rapid. This rapid image rotation-elimination method can be used in fields that require higher image rotation-elimination processing speeds.
Retina-like sensor is a kind of anthropomorphic visual sensor, which mimic the distribution of photoreceptors in the human retina. They are applied in fields of machine vision and target tracking. However, there are few reports on retina-like sensor used for forward-motion imaging. During forward-motion imaging, as the objects being imaged move along the optical axis direction during the integration time, image quality becomes worse towards the border of the image. In order to get clearer image, retina-like sensor are trying to be designed based on the feature of forward-motion imaging. In this paper, firstly, the degraded law of rectilinear sensor used for forward-motion imaging is analyzed, the retina-like sensor model based on the feature of forward-motion imaging are proposed. Secondly, the output image of retina-like sensor and rectilinear sensor used during the forward-motion imaging for different scenes at different degeneration degrees are simulated, respectively. Thirdly, the simulated images of both two sensors are assessed by four different image quality assessment methods including visual information fidelity (VIF), complex wavelet structural similarity index (CW-SSIM), Gabor filtered image contrast similarity (GFCS) and peak signal to noise ratio (PSNR), besides, the data amount of two sensors are compared. Four image quality assessments all demonstrate that image quality of retina-like sensor based on the feature of forward motion imaging is superior to that of rectilinear sensor.
The retina-like sensor is a kind of anthropomorphic visual sensor. It plays an important role in both biological and machine vision due to its advantages of high resolution in the fovea, a wide field-of-view, and minimum pixel count. The space-variant property of the sensor makes it difficult to directly measure its modulation transfer function (MTF). The MTF of a retina-like sensor is measured with the bar-target pattern method. According to the pixel arrangement, the sensor is divided into rings and the MTF of each ring is measured using spoke targets with different periods. Comparison between the measured MTF and the theoretical MTF of the sensor showed that they coincide. The differences between them are also analyzed and discussed. The measured MTF helps to analyze the performance of an imaging system containing a retina-like sensor.
Retina-like sensors maximize both field of view and resolution in addition to economizing on pixel count, so they play an important role in both biological and machine vision. A new retina-like sensor model for compensating motion blur introduced by forward motion imaging is proposed. Next, the determination of pixel arrangement of a retina-like sensor according to visual task requirements is formulated into a multiobjective optimization problem. Then, three retina-like sensors are designed to meet different visual task requirements using the particle swarm optimization algorithm. The results are robust and approximate to design criteria.
A method of encoding eight objects simultaneously in a detour computer generated hologram(CGH) is
proposed. In the method, we divide eight objects into two groups and multiple objects are encoded
through synthesized spectrum. The simulation demonstrated the effectiveness of the method. In the
reconstruction two groups of objects were reconstructed around the same diffraction order along x, y directions, respectively. The result showed that the method can improve the information capacity in
a CGH efficiently.
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