Physical-based optimization for non-physical image dehazing methods

Images captured under hazy conditions (e.g. fog, air pollution) usually present faded colors and loss of contrast. To improve their visibility, a process called image dehazing can be applied. Some of the most successful image dehazing algorithms are based on image processing methods but do not follow any physical image formation model, which limits their performance. In this paper, we propose a post-processing technique to alleviate this handicap by enforcing the original method to be consistent with a popular physical model for image formation under haze. Our results improve upon those of the original methods qualitatively and according to several metrics, and they have also been validated via psychophysical experiments. These results are particularly striking in terms of avoiding over-saturation and reducing color artifacts, which are the most common shortcomings faced by image dehazing methods

Reduksi Kabut pada Citra Kawah Gunung Berapi Kelud Berbasis Dark Channel Prior

Danau kawah gunung berapi aktif Kelud telah terbentuk kembali setelah letusan pada bulan Februari 2014. Beberapa indikator aktivitas gunung berapi adalah adanya perubahan warna, kemunculan gas sulfatara dari sekitar kawah, dan kenaikan ketinggian air kawah. Pengawasan dengan menggunakan kamera CCTV terus dilakukan selama 24 jam. Tujuan utama dari kegiatan pengawasan ini adalah memonitor aktivitas gunung berapi. Hampir setiap saat kondisi kawah tertutup oleh kabut asap sehingga menyulitkan pengawas untuk melakukan observasi terhadap gunung Kelud. Oleh karena itu, dalam penelitian ini metode color attenuation prior berbasis dark channel prior digunakan untuk mengurangi ketebalan kabut. Metode ini menggunakan estimasi peta transmisi dengan menggunakan model kedalaman yang berkorelasi positif antara kedalaman dengan saturasi dan kecerahan. Metode regresi linier least-squared estimation digunakan untuk menentukan parameter koefisien dari model kedalaman. Setelah dilakukan reduksi kabut, kontras dan kecerahan dievaluasi dengan cara mengukur perubahan nilainya. Hasilnya adalah bahwa citra kawah gunung berapi setelah dilakukan reduksi kabut mengalami kenaikan kontras rata-rata sebesar 0.1078 dan penurunan nilai kecerahan sebesar -0.0662. =============================================================================================== The crater lake of Kelud active volcano has reformed after the eruption in February 2014. Several indicators of volcanic activity are the presence of color changes, the emergence of sulfate gases from around the crater, and the rise in the water level of the crater. A supervision was conducted by using CCTV cameras continued for 24 hours. The main purpose of this monitoring activity is to monitor volcanic activity. Almost every time the condition of the crater is covered by smog so that makes it difficult for the observers to make observation on the mountain Kelud. Therefore, in this research we use a method called color attenuation prior based on dark channel prior to reduce fog thickness. This method uses the transmission map estimation by using a depth model that correlates positively between depth with its saturation and brightness. To determine the coefficient parameters of our depth model we use the least-squared estimation linear regression method. We evaluate our results by measuring contrast and brightness changes. The result is that the recovered image of the volcanic crater after the dehazing process has increased value of the average contrast by 0.1078 and the decrease in the brightness value of -0.0662