TY - JOUR
T1 - Image contrast enhancement based on intensity expansion-compression
AU - Liu, Shilong
AU - Rahman, Md Arifur
AU - Lin, Ching-Feng
AU - Wong, Chin Yeow
AU - Jiang, Guannan
AU - Liu, San Chi
AU - Kwok, Ngaiming
AU - Shi, Haiyan
PY - 2017
Y1 - 2017
N2 - In most image based applications, input images of high information content are required to ensure that satisfactory performances can be obtained from subsequent processes. Manipulating the intensity distribution is one of the popular methods that have been widely employed. However, this conventional procedure often generates undesirable artifacts and causes reductions in the information content. An approach based on expanding and compressing the intensity dynamic range is here proposed. By expanding the intensity according to the polarity of local edges, an intermediate image of continuous intensity spectrum is obtained. Then, by compressing this image to the allowed intensity dynamic range, an increase in information content is ensured. The combination of edge guided expansion with compression also enables the preservation of fine details contained in the input image. Experimental results show that the proposed method outperforms other approaches, which are based on histogram divisions and clippings, in terms of image contrast enhancement.
AB - In most image based applications, input images of high information content are required to ensure that satisfactory performances can be obtained from subsequent processes. Manipulating the intensity distribution is one of the popular methods that have been widely employed. However, this conventional procedure often generates undesirable artifacts and causes reductions in the information content. An approach based on expanding and compressing the intensity dynamic range is here proposed. By expanding the intensity according to the polarity of local edges, an intermediate image of continuous intensity spectrum is obtained. Then, by compressing this image to the allowed intensity dynamic range, an increase in information content is ensured. The combination of edge guided expansion with compression also enables the preservation of fine details contained in the input image. Experimental results show that the proposed method outperforms other approaches, which are based on histogram divisions and clippings, in terms of image contrast enhancement.
UR - https://hdl.handle.net/1959.7/uws:64335
U2 - 10.1016/j.jvcir.2017.05.011
DO - 10.1016/j.jvcir.2017.05.011
M3 - Article
SN - 1047-3203
VL - 48
SP - 169
EP - 181
JO - Journal of Visual Communication and Image Representation
JF - Journal of Visual Communication and Image Representation
ER -