We proposed an approach to remove the noise in the γ radiation scene image based on the video time-series correlation considering the challenges of patch noise in the scene images generated using the complementary metal-oxide-semiconductor (CMOS) image sensor in a γ radiation environment. First, according to the foreground patch noise’s background-related and transient characteristics in the γ radiation scene video, which are both included in the time series correlation characteristics, the frame difference and statistical analysis approaches are employed to generate the bright and dark patch noise’s location distribution in the γ radiation scene image from the video sequence image’s residual. Then, through the frame number judgment model designed by the cumulative radiation dose borne using the CMOS image sensor, the adjacent frame images required to effectively repair the current frame image are generated. The effective pixel value is set in the adjacent frame with the same position as the current frame image patch noise and is not affected by radiation interference using the adaptive threshold mechanism and location distribution of bright and dark patch noise and transient characteristics of the patch noise, and the effective pixel value’s mean value is employed to recover the noise pixels. Finally, the Laplacian sharpening filter is used for image postprocessing to enhance the image quality. Experimental results demonstrate that the proposed approach has a higher peak signal-to-noise ratio, structured similarity indexing method value, and subjective perception satisfaction than numerous denoising approaches, which indicates that the approach has higher denoising efficiency and rich detail preservation.