In this paper, a new method based on fusing gradient magnitude (GM) and gradient occurrence (GO) is proposed to construct two new descriptors with high resolution. The suppression normalization descriptor constructs a new descriptor by segmenting the GM and inhibiting the smaller GM. GM-GO fusion descriptor is a new descriptor that fuses GM and GO by suppressing partial GO values (which correspond to a smaller GM) to improve the discriminability of the descriptor. Experimental results show that the two proposed methods have higher matching accuracy under the influences of noise and illumination.