The reconstructed images of biological samples display uneven gray distribution and low contrast, since the synchrotron radiation light source possesses Gaussian distribution characteristics. Moreover, the reconstructed images are also affected by background noise, causing difficulty in observing and analyzing various details of reconstructed images of the biological samples. In order to address this situation, a synchrotron radiation CT image contrast enhancement method, based on image reconstruction, is proposed in this paper. First, the filtered back projection (FBP) reconstruction algorithm and simultaneous algebra reconstruction technique (SART) algorithm are used to reconstruct the image respectively, and the reconstructed numerical range of the two algorithms is obtained; then, the numerical interval reconstructed by the FBP algorithm is mapped to the numerical interval reconstructed by the SART. Finally, the image reconstructed by mapping is combined with a content-adaptive image enhancement algorithm to improve the reconstructed image quality. The experimental results demonstrate that the proposed algorithm can not only effectively eliminate the background noise, but also improve the contrast of the reconstructed image; therefore, allowing for more optimal visualization of the details in the reconstructed samples.