When designing linkage mechanisms for motion synthesis, many examples have shown that the optimal kinematic constraint on the task motion contain too large deviation to be approximately viewed as a single rotational or translational pair. In this paper we seek to adopt our previously established motion synthesis framework for the design of cam-linkages for a more accurate realization, while still maintaining a one-DOF mechanism. To determine a feasible cam to lead through the task motion, first a kinematic constraint is identified such that a moving point on the given motion traces a curve that is algebraically closest to a circle or a line. This leads to a cam contour that is simple and smooth to avoid the drawbacks of cam mechanisms. Additional constraints could also be imposed to specify the location and/or size of the cam-linkages. An example of the design of a lower-limb rehabilitation device has been presented in the end of this paper to illustrate the feasibility of our approach. It is shown that our design could lead the user through a normal walking motion.
To improve the spatial resolution of low resolution image with Gaussian blur and Pepper & salt noise, a blind single-image super resolution reconstruction method is proposed. In the low resolution imaging model, the Gaussian blur, down-sampling, as well as Pepper & Salt noise are all considered. Firstly, the Pepper & Salt noise in the low resolution image is reduced through median filtering method. Then, the Gaussian blur of the de-noised image is estimated through error-parameter analysis method. Finally, super resolution reconstruction is carried out through iterative back projection algorithm. Experimental results show that the Gaussian blur is estimated with high accuracy, and the Pepper & Salt noise are removed effectively. The visual effect and peak signal to noise ratio (PSNR) of the super resolution reconstructed image is improved. In addition, the importance of Gaussian blur in single-image super resolution reconstruction is justified in an experimental way.
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