Divergent thinking (DT) is an important constituent of creativity that captures aspects of fluency and originality. The literature lacks multivariate studies that report relationships between DT and its aspects with relevant covariates, such as cognitive abilities, personality traits (e.g. openness), and insight. In two multivariate studies (N = 152 and N = 298), we evaluate competing measurement models for a variety of DT tests and examine the relationship between DT and established cognitive abilities, personality traits, and insight. A nested factor model with a general DT and a nested originality factor described the data well. In Study 1, DT was moderately related with working memory, fluid intelligence, crystallized intelligence, and mental speed. In Study 2, we replicate these results and add insight, openness, extraversion, and honesty-humility as covariates. DT was associated with insight, extraversion, and honesty-humility, whereas crystallized intelligence mediated the relationship between openness and DT. In contrast, the nested originality factor (i.e. the specificity of originality tasks beyond other DT tasks) had low variance and was not meaningfully related with any other constructs in the nomological net. We highlight avenues for future research by discussing issues of measurement and scoring.

Image enhancement is one of the challenging issues in low level image processing. The main aim of image enhancement is to enhance quality of the image so that visual appearance can be improved. Contrast enhancement is an important factor for image enhancement. Histogram based techniques are one of the most important image processing techniques that are used for enhancement tasks. Histogram equalization is a very effective approach to contrast enhancement. However, histogram equalization tends to change the brightness of the image. The present paper describes a review of different local and global contrast enhancement techniques for a digital image.

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Recent empirical evidence reveals that creative idea generation builds upon an interplay of multiple neural networks. Measures of temporal complexity yield important information about the underlying mechanisms of these co-activated neural networks. A few neurophysiological studies investigated brain signal complexity (BSC) during the production of creative verbal associations and resting states, aiming to relate it with creative task performance. However, it is unknown whether the complexity of brain signals can distinguish between productions of typical and original verbal associations. In the present study, we investigated verbal creativity with multiscale entropy (MSE) of electroencephalography (EEG) signals, which quantifies complexity over multiple timescales, capturing unique dynamic features of neural networks. MSE was measured in verbal divergent thinking (DT) states while emphasizing on producing either typical verbal associations or original verbal associations. We hypothesized that MSE differentiates between brain states characterizing the production of typical and original associations and is a sensitive neural marker of individual differences in producing original associations. Results from a sample of N = 92 young adults revealed slightly higher average MSE for original as compared with typical association production in small and medium timescales at frontal electrodes and slightly higher average MSE for typical association production in higher timescales at parietal electrodes. However, measurement models failed to uncover specificity of individual differences as MSE in typical vs. original associations was perfectly correlated. Hence, individuals with higher MSE in original association condition also exhibit higher MSE during the production of typical associations. The difference between typical and original association MSE was not significantly associated with human-rated originality of the verbal associations. In sum, we conclude that MSE is a potential marker of creative verbal association states, but replications and extensions are needed, especially with respect to the brain-behavior relationships.