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Grayscale image fusion is an important part of the digital image processing field, which is important for the integration of image information. This paper proposes a hybrid algorithm that addresses the problem of unclear edges caused by traditional image fusion algorithms. The proposed algorithm combines the discrete fractional wavelet transform with multi-scale morphology and the pulse coupled neural network. The hybrid algorithm employs discrete fractional wavelet transform to decompose the source images and obtain subbands that include both high- and low-frequency components. An image enhancement method, enhanced by multi-scale morphological operations, is developed to process the low-frequency subband. Additionally, a simplified pulse coupled neural network method is employed to adapt the high-frequency components and generate the high-frequency decision map. Fused images show that proposed algorithm effectively suppresses the Gibbs effect. Simulation experiments confirm that the fusion effect of the hybrid algorithm in this paper is better than the existing five classical algorithms, indicating that the hybrid algorithm is an efficient grayscale image fusion method. [ABSTRACT FROM AUTHOR]

Under uneven lighting conditions, power inspection (PI) images captured by drones exhibit low contrast, lost details and severe noise, which affects the efficiency of monitoring. In response to these issues, this paper proposes a new method for enhancing PI images based on discrete fractional wavelet transform (DFRWT). Firstly, according to the image entropy feature, an appropriate fractional order of DFRWT is selected to decompose the PI image. Secondly, we introduce a low-frequency fusion enhancement method based on complex number domain. It employs different mapping functions to enhance the brightness and contrast of PI image, then the results are combined to reconstruct a new low-frequency component. Here, an improved quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to determine the optimal parameters of the functions, preventing over-enhancement. Finally, an adaptive threshold function is applied to handle noise and edge coefficients in high-frequency components. Using 5 quality metrics to evaluate 8 existing algorithms on 9 datasets, the results indicate that the proposed algorithm can effectively enhance the clarity of PI images, performing excellently in noise suppression and edge detail enhancement. [ABSTRACT FROM AUTHOR]

This letter proposes an indirect power dissipation level short circuit protection (IPDL-SCP) method for silicon carbide (SiC) metal-oxide semiconductor field-effect transistors (mosfets). Due to differences between normal conducting and short-circuit (SC) conditions, this method is triggered by the voltage oscillation vss at the parasitic inductance (Lss) of the source and directly monitoring vds of SiC mosfet. For verification, the short circuit protection circuit is tested and proved functional on the SC test bench. Experimental results show that the protection circuit can respond to both hard switching fault (HSF) and fault under load (FUL), while the fastest response delays are 75 ns for HSF and 170 ns for FUL. Comparisons with other commonly used SC protection methods have also been made, which show that the proposed IPDL-SCP method has better performance in shorter protection delays. [ABSTRACT FROM AUTHOR]

Gate-oxide degradation has been one of the critical reliability concerns of silicon carbide (SiC) metal–oxide–semiconductor-field-effect transistors (mosfets), which could be monitored through aging-sensitive parameters. In this article, an online gate-oxide degradation monitoring method for planar SiC mosfets is proposed by extracting gate charge time at a specific range of gate voltage. It is based on the findings that the input capacitances of planar SiC mosfets change significantly over gate-oxide degradation, which is theoretically analyzed and experimentally verified. The capacitance variations are converted into the gate charge time as the new aging-sensitive parameter. The new parameter measurement circuit is proposed and integrated into the gate driver module. The article results indicate that the new parameter varies noticeably with gate-oxide degradation and the difference of this parameter caused by junction temperature is much smaller than that caused by degradation. Besides, the parameter is immune to package degradation and load current. The condition monitoring method can be implemented online since the parameter is extracted during the off-state of SiC mosfet devices, which does not affect normal operation. The confirmatory experiment is carried out to verify the correctness of the proposed method. [ABSTRACT FROM AUTHOR]