A persistent spin helix with equal strength of the Rashba and Dresselhaus spin-orbit coupling (SOC) is expected for future spintronic devices due to the suppression of spin relaxation. In this work we investigate the optical tuning of the Rashba and Dresselhaus SOC by monitoring the spin-galvanic effect (SGE) in a GaAs/Al0.3Ga0.7As two dimensional electron gas. An extra control light above the bandgap of the barrier is introduced to tune the SGE excited by a circularly polarized light below the bandgap of GaAs. We observe different tunability of the Rashba- and Dresselhaus-related SGE currents and extract the ratio of the Rashba and Dresselhaus coefficients. It decreases monotonously with the power of the control light and reaches a particular value of ∼−1, implying the formation of the inverse persistent spin helix state. By analyzing the optical tuning process phenomenologically and microscopically, we reveal greater optical tunability of the Rashba SOC than that of the Dresselhaus SOC.

Edge detection is often regarded as a basic step in range image processing by virtue of its crucial effect. The majority of existing edge detection methods cannot satisfy the requirement of efficiency in many industrial applications due to huge computational costs. In this paper, a novel instantaneous method, named RIDED-2D is proposed for denoising and edge detection for 2D scan line in range images. In the method, silhouettes of 2D scan line are classified into eight types by defining a few new coefficients. Several discriminant criteria on large noise filtering and edge detection are stipulated based on qualitative feature analysis on each type. Selecting some feature point candidates, a practical parameter learning method is provided to determine the threshold set, along with the implementation of an integrated algorithm by merging calculation steps. Because all the coefficients are established based on distances among the points or their ratio, RIDED-2D is inherently invariant to translation and rotation transformations. Furthermore, a forbidden region approach is proposed to eliminate interference of the mixed pixels. Key performances of RIDED-2D are evaluated in detail by including computational complexity, time expenditure, accuracy and stability. The results indicate that RIDED-2D can detect edge points accurately from several real range images, in which large noises and systematic noises are involved, and the total processing time is less than 0.1 millisecond on an ordinary PC platform using the integrated algorithm. Comparing with other state-of-the-art edge detection methods qualitatively, RIDED-2D exhibits a prominent advantage on computational efficiency. Thus, the proposed method qualifies for real-time processing in stringent industrial applications. Besides, another contribution of this paper is to introduce CPU clock counting technique to evaluate the performance of the proposed algorithm, and suggest a convenient and objective way to estimate the algorithm's time expenditure in other platforms.

To improve comprehensive performance of denoising range images, A rule-based instantaneous denoising method for impulsive noise removal (RID-INR) is proposed in this paper. Based on silhouette features analysis for two typical impulsive noise (IN), dropouts and outliers, a few new coefficients are defined to describe their exclusive features. Founded on several discriminant criteria, the principles of dropout IN detection and outlier IN detection are detailed demonstrated. Subsequently, IN denoising is performed by an Index Distance Weighted Mean filter after a nearest non-IN neighbors searching process. Originated from a theoretical model of invader occlusion, variable window technique is presented for enhancing adaptability of our method, accompanying with practical criteria of adaptive variable window size determination. A complete algorithm has been implemented as embedded modules in two self-developed software. A series of experiments on real range images of single scan line are carried out with comprehensive evaluations in terms of computational complexity, time expenditure and denoising quality. It is indicated that the proposed method can not only detect the impulsive noises with high accuracy, but also denoise them with outstanding efficiency, quality, and adaptability. The proposed method is inherently invariant to translation and rotation transformations, since all the coefficients are established based on distances between the points or their ratio. Therefore, RID-INR is qualified for industrial applications with stringent requirements due to its practicality.

In recent years, valleytronics research based on 2D semiconducting transition metal dichalcogenides have attracted considerable attention. On the one hand, strong spin-orbit interaction allows the presence of spin-valley coupling in this system, which provides spin addressable valley degrees of freedom for information storage and processing. On the other hand, large exciton binding energy up to hundreds of millieletronvolts enable excitons to be stable carriers of valley information. Valley polarization, marked by an imbalanced exciton population in two inequivalent valleys (+K and -K), is the core of valleytronics as it can be utilized to store binary information. Motivated by the potential applications, we present a thorough overview of the recent advancements in the generation, relaxation, manipulation, and transport of the valley polarization in nonmagnetic transition metal dichalcogenide layered semiconductors. We also discuss the development of valleytronic devices and future challenges in this field.

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