Video　distortion　seriously　affects　user　experience　and　downstream　tasks.　Existing　video　restoration　methods　still　suffer　from　high-frequency　detail　loss,　limited　spatio-temporal　dependency　modeling,　and　high　computational　complexity.　In　this　letter,　we　propose　a　novel　video　restoration　method　based　on　full-frequency　spatio-temporal　information　enhancement　(FFSTIE).　The　proposed　FFSTIE　includes　an　implicit　alignment　module　for　accurate　recovery　of　high-frequency　details　and　a　full-frequency　feature　reconstruction　module　for　adaptive　enhancement　of　frequency　components.　Comprehensive　experiments　with　quantitative　and　qualitative　comparisons　demonstrate　the　effectiveness　of　our　FFSTIE　method.　On　the　video　deblurring　dataset　DVD,　FFSTIE　achieves　0.75%　improvement　in　PSNR　and　1.08%　improvement　in　SSIM　with　35%　fewer　parameters　and　59%　lower　GMAC　compared　to　VDTR　(TCSVT＇2023),　achieving　a　balance　between　performance　and　efficiency.　On　the　video　denoising　dataset　DAVIS,　FFSTIE　achieves　the　best　performance　with　an　average　of　35.36　PSNR　and　0.9347　SSIM,　surpassing　existing　unsupervised　methods.