Paper Info
Title
BV-G color-image decomposition with its application to Image Processing of a digital color camera
Abstract
This paper extends the BV (Bounded Variation) - G variational nonlinear image-decomposition approach, which is considered to be useful for image processing of a digital color camera, to a genu- ine color-image decomposition approach. For utilizing inter- channel color cross-correlations, this paper introduces TV (Total Variation) norms of color differences and TV norms of color sums into the BV-G energy functionals, and then derives a denoising- type decomposition-algorithm with over-complete wavelet trans- form, through applying the Besov-norm approximation to the variational problem. Our method decomposes a noisy color image without producing undesirable low-frequency colored artifacts in its separated BV-component, and achieves desirable high-quality color-image decomposition, which is robust against colored ran- dom noise. Furthermore, this paper applies this color-image de- composition method to an IP (Image-Processing) - pipeline of a digital color camera, and the application enables the IP-pipeline to adjust a quality trade-off between texture sharpness and noise visibility according to user's taste. To improve the image-decomposition and to remove the low- frequency colored artifacts from the separated BV components, this paper extends the existing BV-G variational image-decomposition approach to a genuine color-image decomposition approach. For utilizing inter-channel color cross-correlations for the image- decomposition, this paper introduces TV (Total Variation) norms of color differences and TV norms of color sums into the energy functional to be minimized, replaces the TV norms by the Besov norms, defined in an over-complete wavelet transform domain, and then derives a new denoising-type alternately iterative decomposi- tion algorithm with over-complete wavelet transform. Our new color-image decomposition method succeeds in decomposing an input color-image without producing the low-frequency colored artifacts in the separated BV component, removes oscillatory tex- tures from the separated BV component almost completely, and achieves high-quality decomposition, which is robust against col- ored random noise. Furthermore, this paper applies our new color-image decom- position method to an IP (image processing) - pipeline of a digital color camera, and experimentally shows the superiority over the existing standard IP-pipeline. Our new IP-pipeline can adjust a trade-off in picture quality between texture sharpness and noise visibility according to user's taste.
Year
Venue
Keywords
2009
EUSIPCO
approximation theory,cameras,image colour analysis,image denoising,image texture,bv-g color-image decomposition,besov-norm approximation,g variational,bounded variation,digital color camera,image processing,noise visibility,texture sharpness,variational problem
Field
DocType
ISBN
Computer vision,Color space,Color histogram,Image processing,Color balance,Color depth,Demosaicing,Artificial intelligence,RGB color model,Mathematics,Color image
Conference
978-161-7388-76-7
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Takahiro Saito110030.46
Daisuke Yamada200.34
Takashi Komatsu311333.96