Satellite remote sensing image often suffers from haze degradation, which deteriorates significantly the effect of data intelligibility and interpretability. Hence, haze removal technique is essential for inferring high quality images with clear visibility to improve the application value of the satellite images. Thin haze removal is a challenging task since the estimation of haze component is easily affected by ground features. To solve the problem, this paper develops an effective haze removal method for a single visible remote sensing image. Firstly, haze is considered as an additive contamination and can be represented by a haze thickness map (HTM). A ground radiance suppressed HTM (GRS-HTM) is then proposed for a more precise estimation of haze distribution. The haze component for each band is calculated via GRS-HTM and can be removed to recover the clear image. Several visible satellite images with different resolutions were tested to validate the effectiveness of the proposed method. The evaluation results with qualitative and quantitative assessments demonstrate that the proposed method is superior to the traditional methods, and can recover a haze-free image with high quality. (C) 2017 Elsevier B.V. All rights reserved.