Image quality assessment (IQA) method is designed to measure the image quality in consistent with subjective ratings by computational methods. In this research, a valid no reference IQA (NR-IQA) method for color blurred image quality assessment is proposed based on local color appearance, e.g., clarity, in CIELAB color space. In the proposed method, the maximum local clarity and the variability of local clarity are combined to evaluate blurry level. The sharpest spot of an image is represented by the maximum clarity and the variability of clarity expresses the variation in the image content. Massive experiments are performed on five publicly available benchmark databases between proposed method and other state-of-the-art NR-IQA method, for the accuracy, complexity, and generalization performance of IQA. The results show that the weight average accuracy SROCC and PLCC of the proposed method can achieve 0.9345 and 0.9379, the direct average accuracy SROCC and PLCC of the proposed method can achieve 0.9331and 0.9357. The commonly evaluation criteria results prove that the proposed method work better than the state-of-the-art and newly NR-IQA methods for the overall performance on blurry images. These results of test and comparison above show that the proposed method is effective and feasible, and the corresponding method has an excellent overall performance.