Vector Valued images such as RGB color Images or multimodal medical images shows a strong interchannel correlation, which is not exploited by most image processing tools. We propose a new notion of treating vector valued image which is based on the angle between the spatial gradients of their channels. Through minimizing a cost functional that penalizes large angles, images with parallel level sets can be obtained. After formally introducing this idea and corresponding cost functional, we discuss their Gateaux derivatives that leads to diffusion-like gradient descent scheme. The parallel level sets are a suitable concept for color image enhancement. Demosaicking with parallel level sets gives visually perfect result for noise levels of images. The proposed functional yields sharper images than the other approaches in comparison.