MTV: modified total variation model for image noise removal

a modified total variation model is proposed for image noise removal

Description

Y. Wang, et al, MTV: modified total variation model for image noise removal, IEE Electronics Letters, vol.47, no.10, pp.592-594, 2011

in this MTV, the diffusion is along the edge direction of the original noisy image(maybe its smoothed version using a Gaussian filter of small scale),it can preserve edge and suppress staircase very well.

this code includes the TV, Perona-Malik, Y-K forth order PDE, and the proposed MTV model.

• Required Products: Image Processing Toolbox
• MATLAB release: MATLAB 6.5.1 (R13SP1)

[Wang YQ]

I will publish the source codes of my other works on PDE,active contour and cardiac image analysis one after another, please pay attention! Thanks a lot!

[Wang YQ]

Dear BMV,

thank you for your interest in my work!

in the getMTV function, ac2 = ac*ac, just ac2 is used,and ac is also designed as an input arg. At the initial stage when I built the program, I think ac may be helpful for future, it is not used at present.

in addition, the MTV can be extended for color image, texture image, and even using the nonlocal strategy.

[bmv]

mtv = getMTV(I,f,a,b,c,ac2,ac,lambda);
ac - unused. Why?

[Wang YQ]

the MTV model is formulated as the EQ.(4) in this Letter, it can also be interpreted as an energy minimization in Eq.(3).

although the paper has been pulished, after thinking for a period of time, I raised the following question:

In fact, it is easy to find the solution of Eq.(3) since the original noisy image is ready and it is not necessary to solve the PDE in Eq(4). On the other hand, the Eq.(4) works very well to find the final result. it seems there is a paradox.

I need someone to comment this paradox, ^-^, thank you !