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Single Image Dehazing Using Color Ellipsoid Prior
Bui, Trung Minh,Kim, Wonha IEEE 2018 IEEE TRANSACTIONS ON IMAGE PROCESSING - Vol.27 No.2
<P>In this paper, we propose a new single-image dehazing method. The proposed method constructs color ellipsoids that are statistically fitted to haze pixel clusters in RGB space and then calculates the transmission values through color ellipsoid geometry. The transmission values generated by the proposed method maximize the contrast of dehazed pixels, while preventing over-saturated pixels. The values are also statistically robust because they are calculated from the averages of the haze pixel values. Furthermore, rather than apply a highly complex refinement process to reduce halo or unnatural artifacts, we embed a fuzzy segmentation process into the construction of the color ellipsoid so that the proposed method simultaneously executes the transmission calculation and the refinement process. The results of an experimental performance evaluation verify that compared with prevailing dehazing methods the proposed method performs effectively across a wide range of haze and noise levels without causing any visible artifacts. Moreover, the relatively low complexity of the proposed method will facilitate its real-time applications.</P>
Histogram-based luminance enhancement for image dehazing
Bui, Minh-Trung,Kim, Won-Ha 한국방송·미디어공학회 2012 한국방송공학회 학술발표대회 논문집 Vol.2012 No.7
Haze is an extreme reason of the reduction of contrast when capturing image in the outdoor. Recently, there are several single image dehazing techniques, but they are not robust in dynamic variations of natural environment caused by the thickness, coverage of haze and appearance of sunlight. In this paper, we propose an effective and robust method to enhance luminance for image dehazing depending on histogram analysis. Compare with conventional methods, our proposal have better performance in term of contrast, and computation time.
Restoring Degradation of Hazy Image in HSI Color Space
Bui, Minh-Trung,Kim, Won-Ha 한국방송·미디어공학회 2012 한국방송공학회 학술발표대회 논문집 Vol.2012 No.11
Haze is an extreme reason of the reduction of contrast when capturing image in the outdoor. Recently, there are several single image dehazing techniques, but they are not robust in dynamic variations of natural environment caused by the thickness, coverage of haze and appearance of sunlight. In this paper, we propose an effective and robust method to restore degradation of hazy image. Compare with conventional methods, our proposal have better performance and computation time.
Single image dehazing by segmenting dark channel prior
Bui, Minh Trung,Kim, Wonha(김원하) 한국방송·미디어공학회 2016 한국방송공학회 학술발표대회 논문집 Vol.2016 No.11
In image dehazing, the existing transmission estimators bring out the halo artifact at boundaries unless they adopt a refinement process with the high computational complexity. We analyze how the existing transmission estimation methods suffer from the halo artifact at the boundaries and observed that the elaborate, high computational refinement processes to remove the halo effect are excessive for dehazing. On the basis of the analysis and observation, we embed a simple segmentation logic in an existing transmission estimator, which is sufficiently accurate for dehazing . The experiment verifies that the proposed method significantly reduces the halo artifact without requiring any refinement process.
A fast single image dehazing method based on statistical analysis
Bui, Minh Trung,Seongbae Bang(방성배),Kim, Wonha(김원하) 한국방송·미디어공학회 2018 한국방송공학회 학술발표대회 논문집 Vol.2018 No.6
In this paper, we propose a new single-image dehazing method. The proposed method constructs color ellipsoids that are statistically fitted to haze pixel clusters in RGB space and then calculates the transmission values through color ellipsoid geometry. The transmission values generated by the proposed method maximize the contrast of dehazed pixels, while preventing over-saturated pixels. The values are also statistically robust because they are calculated from the averages of the haze pixel values. Furthermore, rather than apply a highly complex refinement process to reduce halo or unnatural artifacts, we embed a fuzzy segmentation process into the construction of the color ellipsoid so that the proposed method simultaneously executes the transmission calculation and the refinement process. The results of an experimental performance evaluation verify that compared to prevailing dehazing methods the proposed method performs effectively across a wide range of haze and noise levels without causing any visible artifacts. Moreover, the relatively low complexity of the proposed method will facilitate its real-time applications.