Gradient-Domain Image Reconstruction Framework with Intensity-Range and Base-Structure Constraints
Takashi Shibata, Masayuki Tanaka, Masatoshi Okutomi
This paper presents a novel unified gradient-domain
image reconstruction framework with intensity-range con-
straint and base-structure constraint. The existing method
for manipulating base structures and detailed textures are
classifiable into two major approaches: i) gradient-domain
and ii) layer-decomposition. To generate detail-preserving
and artifact-free output images, we combine the benefits of
the two approaches into the proposed framework by intro-
ducing the intensity-range constraint and the base-structure
constraint. To preserve details of the input image, the pro-
posed method takes advantage of reconstructing the out-
put image in the gradient domain, while the output inten-
sity is guaranteed to lie within the specified intensity range,
e.g. 0-to-255, by the intensity-range constraint. In addition,
the reconstructed image lies close to the base structure by
the base-structure constraint, which is effective for restrain-
ing artifacts. Experimental results show that the proposed
framework is effective for various applications such as tone
mapping, seamless image cloning, detail enhancement, and
image restoration.
Publication
Gradient-Domain Image Reconstruction Framework with Intensity-Range and Base-Structure Constraints
Takashi Shibata, Masayuki Tanaka, Masatoshi Okutomi
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 [
PDF] [
code]
Gradient-domain Image Reconstruction Framework using Chroma-preserving Intensity-range and Base-structure Constraints
Takashi Shibata, Masayuki Tanaka, Masatoshi Okutomi
We present a gradient-domain image reconstruction framework with the chroma-preserving pixel-wise
intensity-range constraint and the base-structure constraint. The existing methods for manipulating
base structures and detailed textures are classifiable into two major streams:
gradient-domain and layer-decomposition. To generate detail-preserving and artifact-free output images,
we combine the two approaches’ benefits into the proposed framework by introducing the chroma-preserving
intensity-range constraint and the base-structure constraint. To preserve details of the input image,
the proposed method takes advantage of reconstructing the output image in the gradient domain, whereas
the output intensity is guaranteed to lie within the specified intensity range by the intensity-range
constraint. The reconstructed image lies close to the base structure by the base-structure constraint,
which is effective for restraining artifacts. Using this chroma-preserving pixel-wise luminance constraint,
the proposed algorithm does not require post-processing such as intensity clipping or rescaling.
The proposed framework directly generates the output luminance, which guarantees that the output RGB
intensities are within the target intensity range, preserving the chromatic component.
Experiments demonstrated that (1) the proposed framework is effective for various applications
such as tone mapping, seamless image cloning, detail enhancement, and image restoration, and
(2) the proposed framework can preserve chroma components compared with the existing methods.
