In this paper, we propose two new detection-estimation based algorithms that effectively remove impulsive noises in severely corrupted color images. The existing methods for enhancing corrupted color images with impulsive noises commonly possess the inherent problems of excessive computing time and smoothing out edges. However, since our proposed algorithms classify corrupted pixels first in each channel or in each pixel and then perform marginal or vector median filtering only for them, are computationally efficient and preserve edges well. In addition, since there are no appropriate criteria to evaluate the performance of impulsive noise detectors for color images, the objective comparison of noise detectors is difficult. Thus, we introduce a new efficiency factor to compare the performance of noise detectors in digital color images. Simulation results show that the proposed algorithms perform better than the existing methods in terms of both objective and subjective evaluat ons.