English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Acquiring clear images is a crucial precondition in many image-related applications, such as wireless sensor network, industrial inspection, and machine vision. In this paper, a multi-scale image adaptive enhancement algorithm for image sensors in wireless sensor networks based on non-subsampled shearlet transform is presented. The images are decomposed into different scales of coefficients. Then the coefficients are enhanced by a non-linear enhancement function. We set two thresholds for this function. One is used to classify the coefficients between the set to be denoised and the set to be enhanced; the other is to control the enhanced intensity of the coefficients. The thresholds are selected adaptively according to the decomposition scale and the standard deviation of the coefficients. The performance of the proposed algorithm is evaluated both objectively and subjectively. And the results show that the visibility of the images is enhanced significantly.

Non-linear adaptive image enhancement in wireless sensor networks based on non-subsampled shearlet transform