The Total Least Squares (TLS) is a denoising approach to take into the small system perturbations, and to restore the noisy images through a linear combination of the image patches. It can handle not only additive noise but also mixture noise. However, it suffers from high computational complexity and low efficiency. To this end, this paper proposes a grid-based denoising algorithm to speed up the TLS algorithm. Firstly, we utilize a mean value method instead of the bilateral filter parameters used in original algorithm to calculate the weight matrix, and then a strategy of making calculation every half patch is applied. It is proved by experiments that the proposed image denoising algorithm is capable of increasing the calculation speed by two orders of magnitude.
For many years, Photovoltaic (PV) solar technology was believed not possible to be cost effective and not even close to the cost for electricity production compared to fossil fuels. Surprisingly, the fact is that low cost but powerful and long-Iasting solar modules can now be mass produced at the scale of over 60GW per year which makes the LCOE (Ievelizedcost of electricity) of latest PV systemcost competitive with any other technologies. Similarly, for ion implant technology in solar applications, which were thought to be too slow and expensive, have been successfully been utilized in current solar cell mass production as weIl as producing of state-of-the-art high efficiency solar cells. The development of ion implant processes for solar cells and the latest high efficiency solar cell results will be presented in this paper.
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