1. A video quality objective assessment method based on a spatiotemporal domain structure, comprising steps of: (1) marking a reference video sequence without distortion as S r , and marking a distorted video sequence, which is obtained after the S r is distorted, as S d ; wherein a total S r frame quantity is F, a total S d frame quantity is also F, and F>1; widths of images in both the S r and the S d are W, and heights of the images in both the S r and the S d are H; defining an image luminance component sequence of the images in the S r as a luminance component sequence of the S r and marking as Y r ; defining a first image chrominance component sequence of the images in the S r as a first chrominance component sequence of the S r and marking as U r ; defining a second image chrominance component sequence of the images in the S r as a second chrominance component sequence of the S r and marking as V r ; defining an image luminance component sequence of the images in the S d as a luminance component sequence of the S d and marking as Y d ; defining a first image chrominance component sequence of the images in the S d as a first chrominance component sequence of the S d and marking as U d ; defining a second image chrominance component sequence of the images in the S d as a second chrominance component sequence of the S d and marking as V d ; wherein widths of images in the Y r , the U r , the V r , the Y d , the U d and the V d are W, and heights of the images in the Y r , the U r , the V r , the Y d , the U d and the V d are H; (2) calculating a spatiotemporal domain gradient magnitude sequence of the Y r with a three-dimensional Prewitt operator and marking as G r , and marking a pixel value of a pixel at a position of (x,y) in a number t frame in the G r as G r (x,y,t), wherein G r ⁡ ( x , y , t ) = ( Y rx ⁡ ( x , y , t ) ) 2 + ( Y ry ⁡ ( x , y , t ) ) 2 + ( Y rt ⁡ ( x , y , t ) ) 2 , Y rx =Y r {circle around (×)}F x , Y ry =Y r {circle around (×)}F y , Y rt =Y r {circle around (×)}F t , similarly, calculating a spatiotemporal domain gradient magnitude sequence of the Y d with the three-dimensional Prewitt operator and marking as G d , and marking a pixel value of a pixel at a position of (x,y) in a number t frame in the G d as G d (x,y,t), wherein G d ⁡ ( x , y , t ) = ( Y dx ⁡ ( x , y , t ) ) 2 + ( Y dy ⁡ ( x , y , t ) ) 2 + ( Y dt ⁡ ( x , y , t ) ) 2 , Y dx =Y d {circle around (×)}F x , Y dy =Y d {circle around (×)}F y , Y dt =Y d {circle around (×)}F t ; wherein an initial value of the t is 1, 1≦t≦F, 1≦x≦W, 1≦y≦H; Y rx (x,y,t) refers to a pixel value of a pixel at a position of (x,y) in a number t frame in a horizontal gradient magnitude sequence Y rx of the Y r , Y ry (x,y,t) refers to a pixel value of a pixel at a position of (x,y) in a number t frame in a vertical gradient magnitude sequence Y ry of the Y r , and Yr rt (x,y,t) refers to a pixel value of a pixel at a position of (x,y) in a number t frame in a temporal gradient magnitude sequence Y rt of the Y r ; Y dx (x,y,t) refers to a pixel value of a pixel at a position of (x,y) in a number t frame in a horizontal gradient magnitude sequence Y dx of the Y d , Y dy (x,y,t) refers to a pixel value of a pixel at a position of (x,y) in a number t frame in a vertical gradient magnitude sequence Y dy of the Y d , and Y dt (x,y,t) refers to a pixel value of a pixel at a position of (x,y) in a number t frame in a temporal gradient magnitude sequence Y dt of the Y d ; a symbol {circle around (×)} is a zeros truncated convolution symbol; after convolution, dimensions of the Y rx , the Y ry and the Y rt are same as a dimension of the Y r , and dimensions of the Y dx , Y dy and Y dt are same as a dimension of the Y d ; F x , F y and F t correspond to a horizontal mask, a vertical mask and a temporal mask of the three-dimensional Prewitt operator; (3) calculating a spatiotemporal domain local gradient similarity between each pixel point in each frame in the S r and a corresponding pixel point in a corresponding frame in the S d ; marking the spatiotemporal domain local gradient similarity between a pixel point at a position of (x,y) in a number t frame in the S r and a pixel point at a position of (x,y) in a number t frame in the S d as G sim (x,y,t); wherein G sim ⁡ ( x , y , t ) = 2 ⁢ G r ⁡ ( x , y , t ) × G d ⁡ ( x , y , t ) + c 1 ( G r ⁡ ( x , y , t ) ) 2 + ( G d ⁡ ( x , y , t ) ) 2 + c 1 , c 1 is a positive constant preventing the fractional from being meaningless; (4) calculating a spatiotemporal domain local color similarity between each pixel point in each frame in the S r and the corresponding pixel point in the corresponding frame in the S d ; marking the spatiotemporal domain local color similarity between the pixel point at the position of (x,y) in the number t frame in the S r and the pixel point at the position of (x,y) in the number t frame in the S d as C sim (x,y,t); wherein C sim ⁡ ( x , y , t ) = 2 ⁢ U r ⁡ ( x , y , t ) × U d ⁡ ( x , y , t ) + c 2 ( U r ⁡ ( x , y , t ) ) 2 + ( U d ⁡ ( x , y , t ) ) 2 + c 2 × 2 ⁢ V r ⁡ ( x , y , t ) × V d ⁡ ( x , y , t ) + c 3 ( V r ⁡ ( x , y , t ) ) 2 + ( V d ⁡ ( x , y , t ) ) 2 + c 3 , U r (x,y,t) refers to a pixel value of a pixel point at a position of (x,y) in a number t frame in the U r , which is also a pixel value of a pixel point at a position of (x,y) in a first chrominance component in a number t frame in the S r ; V r (x,y,t) refers to a pixel value of a pixel point at a position of (x,y) in a number t frame in the V r , which is also a pixel value of a pixel point at a position of (x,y) in a second chrominance component in a number t frame in the S r ; U d (x,y,t) refers to a pixel value of a pixel point at a position of (x,y) in a number t frame in the U d , which is also a pixel value of a pixel point at a position of (x,y) in a first chrominance component in a number t frame in the S d ; V d (x,y,t) refers to a pixel value of a pixel point at a position of (x,y) in a number t frame in the V d , which is also a pixel value of a pixel point at a position of (x,y) in a second chrominance component in a number t frame in the S d ; c 2 and c 3 are positive constants preventing the fractional from being meaningless; (5) calculating a spatiotemporal domain local similarity between each pixel point in each frame in the S r and the corresponding pixel point in the corresponding frame in the S d according to the spatiotemporal domain local gradient similarity between each pixel point in each frame in the S r and the corresponding pixel point in the corresponding frame in the S d , and the spatiotemporal domain local color similarity between each pixel point in each frame in the S r and the corresponding pixel point in the corresponding frame in the S d ; marking the spatiotemporal domain local similarity between the pixel point at the position of (x,y) in the number t frame in the S r and the pixel point at the position of (x,y) in the number t frame in the S d as Q LS (x,y,t), wherein Q LS (x,y,t)=G sim (x,y,t)×(C sim (x,y,t)) λ , λ is used for adjusting weights of color components, λ>0; (6) calculating an objective quality value of each frame in the S d with a variance fusion method, and marking the objective quality value of the number t frame in the S d as Q frame (t), wherein Q frame ⁡ ( t ) = 1 W × H ⁢ ∑ x = 1 W ⁢ ⁢ ∑ y = 1 H ⁢ ⁢ ( Q LS ⁡ ( x , y , t ) - Q mean ⁡ ( t ) ) 2 , Q mean (t) refers to an average value of the spatiotemporal domain local similarity between all pixel points in the number t frame in the S r and all pixel points in the number t frame in the S d , Q mean ⁡ ( t ) = 1 W × H ⁢ ∑ x = 1 W ⁢ ⁢ ∑ y = 1 H ⁢ ⁢ Q LS ⁡ ( x , y , t ) ; and (7) calculating an objective quality value of the S d with a temporal domain weighting method and marking as Q, wherein Q = 1 F ⁢ ∑ t = 1 F ⁢ ⁢ ( Q LP ⁡ ( t ) × log ⁡ ( γ + t + 1 ) ) , ⁢ Q LP ⁡ ( t ) = { Q frame ⁡ ( t ) , if ⁢ ⁢ t = 1 Q LP ⁡ ( t - 1 ) + α × Δ ⁢ ⁢ Q frame ⁡ ( t ) , if ⁢ ⁢ 2 ≤ t ≤ F ⁢ ⁢ and ⁢ ⁢ Δ ⁢ ⁢ Q frame ⁡ ( t ) ≤ 0 Q LP ⁡ ( t - 1 ) + β × Δ ⁢ ⁢ Q frame ⁡ ( t ) , if ⁢ ⁢ 2 ≤ t ≤ F ⁢ ⁢ and ⁢ ⁢ Δ ⁢ ⁢ Q frame ⁡ ( t ) > 0 , ΔQ frame (t)=Q frame (t)−Q LP (t−1), α refers to a weight during quality increase and β refers to a weight during quality decrease, γ is used to adjust a strength of a recency effect.