An adaptive compressed sampling approach for color images is proposed based on extended wavelet tree theory and multitask Bayesian model. Exploiting the relationship of parent-children coefficients and sibling coefficients in extended wavelet trees, the images in the red, green, blue channels of the color images are adaptively compressed. Exploiting the correlation of the three channels of color images and multitask Bayesian model, the sampled high frequency wavelet coefficients of three channels are dealt, respectively, and then the color images are reconstructed and fused. The research results show that when the sampling times are 600 and the sampling rate is 14.6%, the peak signal to noise ratio values of the colored reconstructed images obtained by proposed method are all above 27 dB, while the mean value of color difference is the least, the color difference values tend to be stable, and the color consistency and stability of the images can be kept well.