In this talk,I will introduce a new primal-dual algorithm for minimizing f(x)+g(x)+h(Ax),where f,g,and h are convex functions,f is differentiable with a Lipschitz continuous gradient,and A is a bounded linear operator.This new algorithm has the Chambolle-Pock and many other algorithms as special cases.It also enjoys most advantages of existing algorithms for solving the same problem.Then I will show some examples in image processing that this algorithm can be applied.