In the lossless compression schemes of the H.26X series video coding standards

the residuals obtained by intra-frame prediction still retain strong spatial correlation and directly participating in entropy coding will lead to the decrease in coding efficiency. Unlike natural images

intra-frame prediction residuals contain rich edge features. To utilize the special spatial correlation of residuals

further reducing its spatial redundancy and improving the intra-frame coding efficiency

a universal lossless intra-frame coding algorithm based on residual median edge detection was proposed. The algorithm first performed edge detection on the intra-frame prediction residuals step by step. By analyzing the numerical features of the adjacent residuals

the median edge detection algorithm was applied to obtain new prediction value. Then

new prediction residual was obtained by comparing prediction value and original residual value. Finally

according to whether the energy of the current coding unit was reduced

it could quickly determine whether to use the new residuals for entropy coding

so as to ensure that the coding of the new prediction residuals could improve the compression ratio. Experimental results show that the coding units processed by this algorithm had lower spatial redundancy and residual energy

thereby reducing the bit-rate after entropy coding. Applying the proposed algorithm in H.265 and the latest H.266 standards

the average energy of residuals decreased by 67.9%

and the average bit-rate reduced by 7.04% and 5.98% respectively

while the codec time changed slightly

with significant practical value.