Noise Suppression in ATMS Spatial Resolution Enhancement Using Adaptive Window Method

Author(s):  
Jun Zhou ◽  
Hu Yang
Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 605
Author(s):  
Da-Zhi Sun ◽  
Ji-Dong Zhong ◽  
Hong-De Zhang ◽  
Xiang-Yu Guo

A basic but expensive operation in the implementations of several famous public-key cryptosystems is the computation of the multi-scalar multiplication in a certain finite additive group defined by an elliptic curve. We propose an adaptive window method for the multi-scalar multiplication, which aims to balance the computation cost and the memory cost under register-constrained environments. That is, our method can maximize the computation efficiency of multi-scalar multiplication according to any small, fixed number of registers provided by electronic devices. We further demonstrate that our method is efficient when five registers are available. Our method is further studied in detail in the case where it is combined with the non-adjacent form (NAF) representation and the joint sparse form (JSF) representation. One efficiency result is that our method with the proposed improved NAF n-bit representation on average requires 209n/432 point additions. To the best of our knowledge, this efficiency result is optimal compared with those of similar methods using five registers. Unlike the previous window methods, which store all possible values in the window, our method stores those with comparatively high probabilities to reduce the number of required registers.


2015 ◽  
Vol 713-715 ◽  
pp. 1926-1930 ◽  
Author(s):  
Jie Liu ◽  
Yi Fan Zhang

In this paper, a wavelet-based Bayesian fusion framework is presented, in which a low spatial resolution hyperspectral (HS) image is fused with a high spatial resolution multispectral (MS) image. Particularly, a multivariate model, Gaussian Scale Mixture (GSM) model, is employed, which is believed to be capable of modeling the distribution of wavelet coefficients more accurately. A practical implementation scheme is also presented for feasible calculations. The proposed approach is validated by simulation experiments for HS and MS image fusion. The experimental results of the proposed approach are also compared with its counterpart employing a Gaussian model for performance evaluation.


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