Color information of natural images can be considered as a highly correlated vector space. Many different color spaces have been proposed in the literature with different motivations toward modeling and analysis of this stochastic field. Recently, color transfer among different images has been under investigation. Color transferring consists of two major categories: colorizing grayscale images and recoloring colored images. The literature contains a few color transfer methods that rely on some standard color spaces. In this paper, taking advantages of the principal component analysis (PCA), we propose a unifying framework for both mentioned problems. The experimental results show the efficiency of the proposed method. The performance comparison of the proposed method is also given.

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Abstract-In this paper, we discuss the information-theoretic approach to finding the pattern of transmission powers of the stations in a CDMA system which maximizes the aggregate capacity of the reverse link. This optimization problem is solved subject to a set of constraints. Previous research has suggested a minimum guaranteed quality of service plus bounds on individual transmission powers and the aggregate transmitted power as the constraints. Solving this problem, it is found out that the solution is very prone to including one station which transmits at a rate a hundred times as much as the others. Thus, it is concluded that the above constraints are not enough to produce a solution which can be realized in an actual system. It is suggested that lack of any constraint which explicitly controls either the maximum capacity of each station or the unfairness of the whole system is responsible for this shortcoming. In this paper, we include a maximum capacity constraint into the formulation and propose an algorithm for solving the resulting optimization problem. Then, empirical evidence are analyzed to show that the system actually becomes more balanced and practical after the new constraint is added to it.