This paper presents an image deblurring method using 0-norm based deblurring and 2-norm based textureaware image fusion for remote sensing images. To restore the details of blurred texture, the proposed method first perform texture restoration by fusing the restored results using Richardson-Lucy deconvolution and unsharp masking. Next, we analyzed the intensity and dark channel properties of remote sensing images and perform the 0-norm based deblurring using the intensity and dark channel priors. Although the 0-norm based deblurring can provide a significantly restored result, it cannot overcome the loss of the texture region. On the other hand, the proposed 2norm based image fusion method can preserve both sharp edges and texture details. In the experiments, we demonstrate that the proposed method can provide better restored results than existing state-of-the-art deblurring methods without over-smoothing and undesired artifact.
This paper presents a torque vectoring algorithm that enhances the agility and stability of a hybrid drive vehicle that is a rear-wheel-drive vehicle equipped with two front in-wheel motors and an open differential at the rear axle. Vehicle agility and stability are closely related to the understeer gradient and the yaw rate damping coefficient. Based on this relation, the proposed torque vectoring algorithm is designed to modify the two cornering characteristics using steady-state and transient control inputs, each input with its respective purpose. Firstly, the steady-state control input improves vehicle agility by reducing the vehicle understeer gradient. Secondly, the transient control input improves the lateral stability by increasing the yaw rate damping coefficient. The effects of the proposed algorithm on vehicle dynamic responses are analyzed to select proper design parameter values for the algorithm. The proposed algorithm has been validated via both computer simulations and vehicle tests. From the simulation results, the proposed control algorithm showed better control performance compared to that of the sliding mode based yaw rate controllers, fulfilling the objectives of the steady-state and transient control strategies. The vehicle tests have been conducted with the algorithm implemented in a rear-wheel-drive vehicle equipped with two front in-wheel motors. The vehicle test results show that the proposed algorithm can provide superior performance in enhancing vehicle agility and stability compared to that of the uncontrolled case.
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