TY - GEN
T1 - A variational method for expanding the bit-depth of low contrast image
AU - Qiao, Motong
AU - Wang, Wei
AU - Ng, Michael K.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Traditionally, bit-depth expansion is an image processing technique to display a low bit-depth image on a high bit-depth monitor. In this paper, we study a variational method for expanding the bit-depth of low contrast images. Our idea is to develop a variational approach containing an energy functional to determine a local mapping function f(r,x) for bit-depth expansion via a smoothing technique, such that each pixel can be adjusted locally to a high bit-depth value. In order to enhance low contrast images, we make use of the histogram equalization technique for such local mapping function. Both bit-depth expansion and equalization terms can be combined together into the resulting objective function. In order to minimize the differences among the local mapping function at the nearby pixel locations, the spatial regularization of the mapping is incorporated in the objective function. Experimental results are reported to show that the performance of the proposed method is competitive with the other compared methods for several testing low contrast images.
AB - Traditionally, bit-depth expansion is an image processing technique to display a low bit-depth image on a high bit-depth monitor. In this paper, we study a variational method for expanding the bit-depth of low contrast images. Our idea is to develop a variational approach containing an energy functional to determine a local mapping function f(r,x) for bit-depth expansion via a smoothing technique, such that each pixel can be adjusted locally to a high bit-depth value. In order to enhance low contrast images, we make use of the histogram equalization technique for such local mapping function. Both bit-depth expansion and equalization terms can be combined together into the resulting objective function. In order to minimize the differences among the local mapping function at the nearby pixel locations, the spatial regularization of the mapping is incorporated in the objective function. Experimental results are reported to show that the performance of the proposed method is competitive with the other compared methods for several testing low contrast images.
KW - bit-depth expansion
KW - low contrast
KW - spatial regularization
KW - variational methods
UR - http://www.scopus.com/inward/record.url?scp=84884960600&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40395-8_5
DO - 10.1007/978-3-642-40395-8_5
M3 - Conference proceeding
AN - SCOPUS:84884960600
SN - 9783642403941
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 54
EP - 65
BT - Energy Minimization Methods in Computer Vision and Pattern Recognition - 9th International Conference, EMMCVPR 2013, Proceedings
T2 - 9th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2013
Y2 - 19 August 2013 through 21 August 2013
ER -