Perceiving Unknown in Dark from Perspective of Cell Vibration

Low light very likely leads to the degradation of image quality and even causes visual tasks' failure. Existing image enhancement technologies are prone to over-enhancement or color distortion, and their adaptability is fairly limited. In order to deal with these problems, we utilise the mechanism of biological cell vibration to interpret the formation of color images. In particular, we here propose a simple yet effective cell vibration energy (CVE) mapping method for image enhancement. Based on a hypothetical color-formation mechanism, our proposed method first uses cell vibration and photoreceptor correction to determine the photon flow energy for each color channel, and then reconstructs the color image with the maximum energy constraint of the visual system. Photoreceptor cells can adaptively adjust the feedback from the light intensity of the perceived environment. Based on this understanding, we here propose a new Gamma auto-adjustment method to modify Gamma values according to individual images. Finally, a fusion method, combining CVE and Gamma auto-adjustment (CVE-G), is proposed to reconstruct the color image under the constraint of lightness. Experimental results show that the proposed algorithm is superior to six state of the art methods in avoiding over-enhancement and color distortion, restoring the textures of dark areas and reproducing natural colors. The source code will be released at https://github.com/leixiaozhou/CVE-G-Resource-Base.Comment: 13 pages, 17 figure

Low-light Image Enhancement Using Cell Vibration Model

 Low light very likely leads to the degradation of an image's quality and even causes visual task failures. Existing image enhancement technologies are prone to overenhancement, color distortion or time consumption, and their adaptability is fairly limited. Therefore, we propose a new single low-light image lightness enhancement method. First, an energy model is presented based on the analysis of membrane vibrations induced by photon stimulations. Then, based on the unique mathematical properties of the energy model and combined with the gamma correction model, a new global lightness enhancement model is proposed. Furthermore, a special relationship between image lightness and gamma intensity is found. Finally, a local fusion strategy, including segmentation, filtering and fusion, is proposed to optimize the local details of the global lightness enhancement images. Experimental results show that the proposed algorithm is superior to nine state-of-the-art methods in avoiding color distortion, restoring the textures of dark areas, reproducing natural colors and reducing time cost. The image source and code will be released at https://github.com/leixiaozhou/CDEFmethod. </p

Country-Level Correlates of the Dark Triad traits in 49 Countries

Objectives: The Dark Triad traits (i.e., narcissism, psychopathy, and Machiavellianism) capture individual differences in aversive aspects of personality to compliment work on the other taxonomies such as the Big Five traits. However, most studies on the Dark Triad traits rely on samples from English-speaking countries that are relatively advanced in socio-political development (e.g., Westernized).Method: We drew on data from 49 countries (N = 11,723; 65.8% female; AgeMean = 21.53) to examine how a wide net of country-level variables in economic status (e.g., Human Development Index), social relations (e.g., gender equality), political orientations (e.g., democracy), and cultural values (e.g., embeddedness) relate to country-level rates of the Dark Triad traits and variance in the magnitude of sex differences in them.Results: Narcissism was especially sensitive to country-level factors. Countries that had less advanced systems, with more embedded and hierarchical cultural systems, were more narcissistic as a population. Sex differences in narcissism were larger in more advanced societies, because women were less likely to be narcissistic in advanced as opposed to less advanced countries.Conclusions: We discuss the results using evolutionary and social role models of personality and sex differences. In particular, higher nation-level narcissism was more common in “less advanced” places and sex differences in narcissism were larger in “more advanced” places which is more consistent with evolutionary than social role models.</p