Improvement of the automatic gamma correction method in cloud image detection

Abstract

Clouds become an important part of human life and are studied in several disciplines in the form of important analyses in some applications. Examples of application of cloud analysis on solar panels or photovoltaics, accurate weather forecasts, accuracy of rainfall predictions, application in the field of meteorology, imaging of the sky in some cases, air humidity survey, and the case of turbulence on Aircraft caused by clouds cumulonimbus. The structure and shape of the clouds are continuously changing, becoming an interesting part to detect. The cloud detection process can be done by taking several samples of imagery from the cloud and the image processing process is done. Most research processes RGB cloud imagery into HSV cloud imagery, Some research using the image detection method of flying apply the channel's convolution R-B, R/B, ????−????????+????, dan chroma C = max(R, G, B)-min(R, G, B). Gamma correction has an efficient characteristic of storing and dividing imagery by small bits, thus the study proposed an image detection development using automatic gamma correction, with ground truth being Image data from SWIMSEG Nanyang Technological University Singapore. The proposed method in the proposed study obtained a precision value and better computing time with a precision value of 0.93 and a computational time of 0.71 sec.

Modelling spatio-temporal energy consumption from nighttime radiance satellite dataset

“…Applied in the socio-economic field [6]. Modelling of spatial distribution and human population growth [7], overall electricity and energy consumption [8], economic growth rate [9], gas emissions from anthropogenic [10], and estimation of various other parameters [11].…”