基于色彩相关性的彩色图像清晰度评价算法

数字图像的清晰度评价对于相机自动对焦而言至关重要。针对现有清晰度评价函数的不足之处，提出了一种针对彩色数字图像的空域清晰度评价算法。此算法利用像素三刺激值之间的色差相关性判定像素点的色彩，建立清晰度色差因子；运用非线性函数提高了像素点的梯度增益系数，使该评价函数对特殊条件下图像的清晰度判定更敏感。实验证明，该评价函数在评价一般自然图像清晰度时比传统评价算法更为敏感；在典型评价函数评价特殊目标图像失效时，该算法依然具有良好的鲁棒性；此算法计算量较小，执行效率高，易于硬件实现。

Image definition evaluation algorithm based on color relativity

Definition evaluation function of digital image plays an important role in digital camera auto-focus. Due to the existing definition evaluation functions are of some marked disadvantages, a spatial domain evaluation algorithm for digital color image was proposed. The colorful property of each pixel was judged and definition chromatic difference parameters was created by using chromatic difference between their tri-stimulus values. Besides,nonlinear function was used to improve the gradient coefficient of each pixel which made the evaluation function be more sensitive to some images in extreme cases. Experimental results show the superiority of our algorithm over the most of existing evaluation algorithms in dealing with natural images. And our method also is of a good ability of robustness as well as reducing calculation complexity and it can be easily achieved on hardware.