Design Simulation of Automatic Wavelet Based- Nonlinear Image Enhancement Technique for Aerial Imagery

Abstract

Infrared image enhancement is an essential pre-processing technique used by intelligent urban surveillance systems for Smart City applications. Existing grayscale mapping-based methods are susceptible to amplifiying noise, enhancing the background, and distorting brightness. An technique for boosting adaptive infrared images was created to deal with these problems. It is advised that the brightness be adjusted and that the histogram be divided. To begin with, the grayscale histogram is flexible. The histogram was divided into several sub-histograms using a locally weighted scatter plot smoothing approach. The fore- and background sub-histograms are then distinguished by looking at the local minima. based on a recently introduced grayscale density metric. The front sub-histograms are equalized. enhancing local features using a local contrast weighted distribution while using a global contrast weighted distribution. In background sub-histograms, the dynamic range is preserved in its proper proportions. in order to prevent over-enhancement The influence of noise is expected to be lessened in the interim by a visual correction factor that considers the characteristic of the grayscale re-mapping process, human eyesight. Finally, particle swarm optimization is used to adjust the output's mean brightness from a picture that will be used as a reference for actual infrared images. Both qualitative and quantitative analyses were done to show how effective our method is compared to other conventional methods. In addition, to enhance the visual quality of digital images in high-dynamic light scenarios, we have presented a wavelet-based dynamic range compression technique. The quick image enhancement approach, which offers dynamic range compression while preserving the local contrast and tone rendition, is an excellent option for aerial imaging applications like picture interpretation in security and defense activities. Video streaming for aviation safety can also employ this technique. This paper offers the most recent version of the suggested algorithm, which may enhance aerial photos more effectively than through direct human inspection. The algorithm performs well and produces high-quality photos when applied to a range of air images.