Aiming at the problems of noise introducing and color quality degradation in the process of image transmission as well as the loss of image details resulting from the median filtering and the blurring resulting from the mean filtering, an image enhancement and filtering algorithm for CMOS image sensor is proposed in this paper. In this algorithm, the interpolated Bayer image data is enhanced and de-noised in the 1-D space. First, the image is converted from the RGB space to the YUV space, in the Y channel, the improved histogram equalization method is used to realize the contrast enhancement, and the U and V channels are segmented by linear adjustment method to achieve saturation adjustment. Then, the Y channel is de-noised adaptively, and the weighted median filtering is used to reduce the noise in U and V channels so as to meet the demand of the subsequent processing. Finally, on the Y channel, a sharpening mask based on Laplace operator is used to sharpen the details of the image. The experimental results show that, compared with the median and mean filtering, our method achieves better visual effect, well preserved details, higher quality of color and almost no blurring. By comparing the peak signal to noise ratio (PSNR), the PSNR of the proposed algorithm is better than the median and mean filtering and the noise is suppressed effectively. Moreover, the whole algorithm is addressed in 1-D neighborhood; it’s easier to realize on limited hardware with small area and low consumption.