High　Efficiency　Video　Coding　-　Screen　Content　Coding　(HEVC-SCC)　is　an　extension　to　HEVC　which　adds　sophisticated　compression　methods　for　computer　generated　content.　A　video　frame　is　usually　split　into　blocks　that　are　predicted　and　subtracted　from　the　original,　which　leaves　a　residual.　These　blocks　are　transformed　by　integer　discrete　sine　transform　(IntDST)　or　integer　discrete　cosine　transform　(IntDCT),　quantized,　and　entropy　coded　into　a　bitstream.　In　contrast　to　camera　captured　content,　screen　content　contains　a　lot　of　similar　and　repeated　blocks.　The　HEVC-SCC　tools　utilize　these　similarities　in　various　ways.　After　these　tools　are　executed,　the　remaining　signals　are　handled　by　IntDST/IntDCT　which　is　designed　to　code　camera-captured　content.　Fortunately,　in　sparse　coding,　the　dictionary　learning　process　which　uses　these　residuals　adapts　much　better　and　the　outcome　is　significantly　sparser　than　for　camera　captured　content.　This　paper　proposes　a　sparse　coding　scheme　which　takes　advantage　of　the　similar　and　repeated　intra　prediction　residuals　and　targets　low　to　mid　frequency/energy　blocks　with　a　low　sparsity　setup.　We　also　applied　an　approach　which　splits　the　common　test　conditions　(CTC)　sequences　into　categories　for　training　and　testing　purposes.　It　is　integrated　as　an　alternate　transform　where　the　selection　between　traditional　transform　and　our　proposed　method　is　based　on　a　rate-distortion　optimization　(RDO)　decision.　It　is　integrated　in　HEVC-SCC　test　model　(HM)　HM-16.18+SCM-8.7.　Experimental　results　show　that　the　proposed　method　achieves　a　Bjontegaard　rate　difference　(BD-rate)　of　up　to　4.6%　in　an　extreme　computationally　demanding　setup　for　the　＂all　intra＂　configuration　compared　with　HM-16.18+SCM-8.7.