Method for determining a visual quality index of a high dynamic range video sequence

A method for determining a visual quality index of at least one high dynamic range video sequence (HDR sequence), distorted by image processing operations and issued from a reference high dynamic range video sequence, each of the HDR sequence and the reference HDR sequence comprising Nframe video frames t, with N≧2 and tε[1 . . . Nframe], each video frame t comprising a plurality of pixels organized into rows and columns and each pixel having at least a luminance value, the method comprising:

• applying a transformation to the video frames t of the HDR sequence and the reference HDR sequence in order to obtain video frames t of the HDR sequence and the reference HDR sequence in a perceived luminance domain, the transformed luminance values of the video frames t in the perceived luminance domain being substantially linear to the luminance values perceived by the human visual system for the HDR sequence and the reference HDR sequence,
• computing, for each couple of frames t of the HDR sequence and the reference HDR sequence in the perceived luminance domain, Nscale×Norient similarity frames Simt,s,o representative of a perceptual similarity between the frame t of the HDR sequence and the frame t of the reference HDR sequence at different spatial scales s and different spatial orientations o, with sε[1 . . . Nscale] and oε[1 . . . Norient], a similarity value being associated to each pixel of the similarity frame Simt,s,o,
• computing, for each couple of frames t of the HDR sequence and the reference HDR sequence, a global similarity frame Simt based on the computed similarity frames Simt,s,o at the different spatial scales s and the different spatial orientations o,
• pooling, for each group of q consecutive global similarity frames Simt, with q≧2, and for each one of a plurality of spatio-temporal tubes within said group of q consecutive global similarity frames Simt, the similarity values of the pixels included in said spatio-temporal tubes in order to generate a short term error value for each said spatio-temporal tubes, the short term error values of each spatio-temporal tube being included into an error map,
• pooling at least a portion of the short term error values of each error map in order to generate a short term quality score for each group of q consecutive global similarity frames Simt, and
• computing the visual quality index of the HDR sequence based on said short term quality scores.