Nowadays,　objective　image　quality　assessment　(IQA)　issue　becomes　increasingly　important　for　both　the　practical　application　and　scientific　research　in　digital　image　processing　systems.　In　this　paper,　we　conduct　feature　comparison　and　analysis　on　new　challenging　research　fields　including　contrast　distorted,　screen　content,　multiply-distorted,　tone-mapped,　Depth　Image　Based　Rendering　(DIBR)　and　authentically　distorted　IQA.　We　describe　the　performance　criteria,　design　rationale,　and　benchmark　databases　for　validating　IQA　metrics　in　accordance　with　human　perceptions.　Then　we　provide　some　important　conclusions　of　feature　selection　in　terms　of　different　IQA　problems.　In　this　work,　our　goal　is　dominantly　towards　judging　the　robustness　of　mainstream　features　used　in　the　IQA　field,　which　can　help　current　and　emerging　researchers　for　better　and　faster　grasping　the　speciality　of　each　of　novel　IQA　directions　reported.　(C)　2018　Elsevier　Inc.　All　rights　reserved.