In　many　applications,　the　received　image　is　degraded　by　unknown　blur　and　noise.　Traditional　blind　image　deconvolution　algorithms　have　drawback　of　noise　amplification.　For　robustness　against　the　influence　of　noise,　this　paper　proposes　a　novel　blind　image　deconvolution　algorithm　by　combining　the　support　vector　regression　(SVR)　approach　and　the　total　variation　approach.　The　proposed　algorithm　has　a　lower　computational　complexity　and　a　good　performance　in　image　denoising　and　image　deblurring.　Illustrative　examples　show　that　the　proposed　blind　image　deconvolution　algorithm　and　has　better　performance　in　improvement　signal-to-noise　ratio　than　two　traditional　blind　image　restoration　algorithms.　©　Springer-Verlag　Berlin　Heidelberg　2014.