Abstract:
Simulation of film grain in an image can occur by compressing a video image, then transmitting compressed video together with a message containing at least one parameter indicative of the original film grain, to a decoder, and restoring the original grainy appearance of images by having the decoder simulating film grain based on the content of the film grain message. To improve efficiency, one or more parameters of film grain information undergo scaling in accordance with a target pixel block size for pixel blocks in the image. Such scaling allows for the use of conventional circuitry for performing block-based operations in connection with the film grain simulation.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit, under 35 U.S.C. §365 of International Application PCT/US2004/030950, filed Sep. 22, 2004, which was published in accordance with PCT Article 21(2) on Apr. 7, 2005 in English and which claims the benefit of U.S. provisional patent application No. 60/505,260, filed Sep. 23, 2003. 
    
    
     TECHNICAL FIELD 
     This invention relates to a technique for simulating film grain in a coded image following decoding. 
     BACKGROUND ART 
     Motion picture films comprise silver-halide crystals dispersed in an emulsion, which is coated in thin layers on a film base. The exposure and development of these crystals form the photographic image consisting of discrete tiny particles of silver. In color negatives, tiny blobs of dye occur on the sites where the silver crystals form following chemical removal of the silver during development of the film stock. These small specks of dye commonly bear the label ‘grain’ in color film. Grain appears randomly distributed on the resulting image because of the random formation of silver crystals on the original emulsion. Within a uniformly exposed area, some crystals develop after exposure while others do not. 
     Grain varies in size and shape. The faster the film, the larger the clumps of silver formed and blobs of dye generated, and the more they tend to group together in random patterns. The term “granularity” typically refers to the grain pattern. The naked eye cannot distinguish individual grains, which vary from 0.0002 mm to about 0.002 mm. Instead, the eye resolves groups of grains, referred to as blobs. A viewer identifies these groups of blobs as film grain. As the image resolution becomes larger, the perception of the film grain becomes higher. Film grain becomes clearly noticeable on cinema and high-definition images, whereas film grain progressively loses importance in Standard Definition Television (SDTV) and becomes imperceptible in smaller formats. 
     Motion picture film typically contains image-dependent noise resulting either from the physical process of exposure and development of the photographic film or from the subsequent editing of the images. Photographic film possesses a characteristic quasi-random pattern, or texture, resulting from physical granularity of the photographic emulsion. Alternatively, simulation of similar pattern can occur in computed-generated images in order to blend them with photographic film. In both cases, this image-dependent noise bears the designation of “film grain.” Quite often, moderate grain texture presents a desirable feature in motion pictures. In some instances, the film grain provides visual cues that facilitate the correct perception of two-dimensional pictures. Film grade often varies within a single film to provide various clues as to time reference, point of view, etc. Many other technical and artistic demands exist for controlling grain texture in the motion picture industry. Therefore, preserving the grainy appearance of images throughout image processing and delivery chain has become a requirement in the motion picture industry. 
     Several commercially available products have the capability of simulating film grain, often for blending a computer-generated object into natural scene. Cineon® from Eastman Kodak Co, Rochester N.Y., one of the first digital film applications to implement grain simulation, produces very realistic results for many grain types. However, the Cineon® application does not yield good performance for many high speed films because of the noticeable diagonal stripes the application produces for high grain size settings. Further, the Cineon® application fails to simulate grain with adequate fidelity when images become subject to prior processing, for example, such as when the images are copied or digitally processed. 
     Another commercial product that simulates film grain is Grain Surgery™ from Visual Infinity Inc., which is used as a plug-in of Adobe® After Effects®. The Grain Surgery™ product appears to generate synthetic grain by filtering a set of random numbers. This approach suffers from disadvantage of a high computational complexity. 
     Film grain simulation continues to remain a topic of interest. Recently, the H.264 Video Compression standard underwent amendment to adopt a standard Supplemental Enhancement Information (SEI) message specifying film grain simulation parameters. The adoption of a specific format film grain SEI message will greatly facilitate the development of decoders for simulating film grain using a technique recently disclosed by the assignee of the instant application for simulating film grain. The technique developed by applicants&#39; assignee simulates film grain by (1) first filtering grain out of images before compression, then (2) transmitting compressed video together with a message containing information about original grain to a decoder, and (3) restoring the original grainy appearance of images by having the decoder simulating film grain based on the content of the SEI message. This technique provides large bit-rate savings for high quality applications requiring the film grain preservation. However, the technique increases decoder complexity since film grain generation requires the creation of the film grain image by operating on blocks of 16×16 pixels, and subsequent deblocking of 16×16 block edges of the film grain image. 
     Thus, a need exists for a film grain simulation technique that overcomes the prior disadvantages by providing greater efficiency. 
     BRIEF SUMMARY OF THE INVENTION 
     Briefly, in accordance with a preferred embodiment of the present principles, a method is provided for simulating film grain. The method commences upon the receipt of image information and the receipt of film grain information that includes at least one parameter among a set of possible parameters specifying different attributes of the film grain previously in the image. Using a film grain model, grain simulation occurs in accordance with the at least one parameter which is scaled in accordance with a target, pixel block size for pixel blocks in the image. The simulated film grain is then merged into the image. 
     Scaling the film grain information in accordance with a target pixel block size allows for the use of arbitrary block sizes, which permits the use of conventional hardware elements to perform the block-based operations associated with film grain simulation. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  depicts a block schematic diagram of a system for simulating film grain; 
         FIG. 2  depicts a flow chart that shows the steps of a method by which the system of  FIG. 1  generates film grain information in accordance with a first aspect of the present principles; 
         FIG. 3  depicts a flow chart that shows the steps of a method by which the system of  FIG. 1  generates film grain information in accordance with a second of the present principles; 
         FIG. 4  depicts an example of an 8×8 pixel block scaled in accordance with the present principles; 
         FIG. 5A  depicts an example of an 8×8 pixel block whose vertical edges only undergo scaling; and 
         FIG. 5B  depicts an example of an 8×8 pixel blocked whose horizontal edges only undergo scaling. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  depicts a block schematic diagram of a system  10  for simulating film grain in an image. The system  10  comprises a first block  12  for generating film grain information from both an input image  104 , and from at least one film grain parameter embodied in a film grain message, such as SEI message  106 . The film grain generator block  12  generates film grain information from such input information using one of the methods of  FIGS. 2 and 3  described in greater detail below. The film grain information generated by the film grain generator block  12  undergoes deblocking by a film grain deblocking filter  14  before receipt at a blending block  16 . The blending block  16  blends the filtered film grain information with the input image to yield an output image containing film grain. 
       FIG. 2  depicts a flow chart illustrating the steps of a method in accordance with a first aspect of the present principles for film grain generation. As described in greater detail below, the method of  FIG. 2  operates to generate the film grain from Gaussian noise scaled prior to frequency filtering. The film grain generation method of  FIG. 2  commences upon execution of step  100  during which the system variables undergo initialization. Following step  100 , extraction of successive N×M pixel blocks from the input image  104  occurs, with N and M each being integers greater than zero. 
     Following step  102 , step  105  occurs and a noise generator (not shown) within the film grain generator block  12  of  FIG. 1  generates random (Gaussian) noise in accordance with at least one of the film grain parameters contained in the SEI message  106  that accompanies the input image, as scaled in the manner discussed below. As adopted in the H.264 compression standard, the film grain parameters in the SEI message  106  are predicated on a 16×16 pixel block. Such a block size does not always afford the greatest convenience in terms of implementation efficiency. 
     In accordance with the present principles, the film grain parameters in the SEI message undergo scaling during step  107  to allow simulation of film grain with block sizes other than 16×16 pixels. In practice, the SEI message defines various film parameters, including, two sets of cut frequencies, namely the horizontal and vertical low cut frequencies and the horizontal and vertical high cut frequencies. To appreciate the manner in which the SEI parameters, and in particular, the horizontal and vertical high cut and low cut frequencies, undergo scaling, let N s ×M s  represent the original block size (i.e., 16×16 pixels), and let N t ×M t  represent the target block size on which the new scaled parameters will operate. The horizontal and vertical high cut frequencies undergo scaling as follows: 
                     f   t   HH     =     ceil   ⁡     (         N   t       N   s       ⁢     f   s   HH       )               (   1   )                 f   h   HH     =     ceil   ⁡     (         M   t       M   s       ⁢     f   s   HV       )               (   2   )               
with the function f ceil (x) returning the smallest integer larger or equal than x, f t   HH  is the new high horizontal cut frequency and f t   HV  is the new high vertical cut frequency for use with the target block size. This scaling constitutes the equivalent of dividing the original frequency by the ratio of block sizes and rounding up to the nearest integer. Analogously, the horizontal and vertical low cut frequencies undergo scaling as follows:
 
                     f   t   LH     =     floor   ⁡     (         N   t       N   s       ⁢     f   s   LH       )               (   3   )                 f   t   LV     =     floor   ⁡     (         M   t       M   s       ⁢     f   s   LV       )               (   4   )               
where floor (x) returns the greatest integer smaller or equal than x, f t   LH  is the new low horizontal cut frequency and f t   LV  is the new low vertical cut frequency to be used with the target block size. This scaling constitutes the equivalent of dividing the original frequency by the ratio of block sizes and rounding down to the nearest integer.
 
     The above-described rounding yields the most similar film grain on the target block size as compared to the film grain resulting from using the original cut frequency values defined on blocks of 16×16 pixels. However, any type of rounding (floor, ceil or nearest integer) could (also scale both horizontal and vertical cut frequencies. 
     In the illustrated embodiment, the original blocks are 16×16 pixels and the target blocks are 8×8 pixels. Under such circumstances, the scaling of the high cut frequencies can occur as follows:
 
 f   t   H =( f   0   H +1)&gt;&gt;1  (5)
 
where f t   H  represents the new high cut frequency. Equation (5) can scale both horizontal and vertical high cut frequencies because source and target blocks are squared. The scaling of the low cut frequencies becomes:
 
f t   L =f 0   L &gt;&gt;1  (6)
 
where f t   L  represents the new low cut frequency. Analogously, equation (6) can scale both horizontal and vertical low cut frequencies.
 
     The parameters of the SEI message can undergo scaling to any desired block size, allowing efficient implementation of the film grain simulation algorithms described previously. In the illustrated embodiment, scaling the film grain parameter values to 8×8 pixel blocks, allows the reuse of many existing integrated circuits for performing hardware accelerated Discrete Cosine Transform (DCT), Inverse Discrete Cosine Transform (IDCT) and other block-based operations. 
     During step  108 , the random noise undergoes scaling to change the pixel values of the N×M pixel block that is already in the final size (for instance, 8×8) to avoid/reduce the complexity of the deblocking process. The scaling that occurs during step  108  takes the form of modifying the variance of the noise with respect to the value (as scaled) specified in the SEI message. Assume that for a given block B, the random noise generated during step  105  has a mean μ and variance σ 2 . Given the scaling function S B , defined for each pixel of the block B, the scaled pixel value will have the following relationship:
 
 B   scaled ( i,j )=( B ( i,j )−μ)· S ( i,j )+μ  (7)
 
where B(i, j) represents the pixel at coordinates (i, j) of block B. Observe that Equation (7) only applies to those pixels where S(i, j) is not 1.
 
     The noise scaling that occurs during step  108  obviates the need for a deblocking filter in order to reduce blocking artifacts. The use of noise scaling to reduce such artifacts makes use of the principle that blocking artifacts arise as a result of uncorrelated pixels across block edges. To reduce such artifacts, the correlation across bock edges has to be increased, which is equivalent to reducing the amount of noise on block edges. 
     Follow step  108 , the scaled random noise undergoes a Discrete Cosine Transform during step  110 . Thereafter, the coefficients become frequency filtered during step  112  in accordance with a corresponding filter parameter in the SEI message  106 . An Inverse Discrete Cosine Transformation (IDCT) is performed during step  114 . During step  116 , a check occurs to determine whether additional N×M pixel blocks remain unread. If no further blocks remain, the resultant noise forms a film grain image  118 , and the process ends during step  120 . Otherwise, step  102  and those following it undergo re-execution until no further unread N×M blocks remain from the input image  104 . 
       FIG. 3  depicts a flow chart illustrating the steps of a method in accordance with a second aspect of the present principles for film grain generation. The film grain generation method of  FIG. 3  includes many of the same steps as the method of  FIG. 2  and like numbers appear in  FIG. 3  to reference like steps. The film grain generation method of  FIG. 3  differs from the method of  FIG. 2  with regard to the occurrence of noise scaling. As described, the film generation method of  FIG. 2  undertakes noise scaling during step  108  as a prelude to the frequency filtering that occurs during step  112 . In contrast, the film generation method of  FIG. 3  undertakes noise scaling during step  115  subsequent to the Inverse Discrete Cosine Transform that occurs during step  114 , after the frequency filtering performed during step  112 . The scaling operation applied to each pixel of the filtered random noise during step  115  of  FIG. 4  occurs in the equivalent manner prescribed by Equation (7). 
     Specification of the scaling function can occur a priori or can occur automatically, based on the parameters of the SEI message  106  and on the block size. The scaling function could also adapt to the different sets of parameters specified in the SEI message. 
     In the illustrated implementation, the scaling function reduces the amount of noise on the block edges (to avoid blocking artifacts) while at the same time increasing the amount of noise inside the block in order to keep the same overall amount of noise. With scaling particularized to 8×8 pixel blocks, the scaling function can achieve the result shown in  FIG. 4  for pixel block  200 . The darkest gray area  202  on the edge of pixel block  200  represents a reduction in the noise (S(i, j)&lt;1), whereas the lightest gray area  204  inside the block represents an increase in the noise (S(i, j)&gt;1). The mid gray region  206  represents no change in the noise intensity (S(i, j)=1). 
     The use of the scaling function constitutes a tradeoff between maintaining the film grain appearance (since the parameters of the SEI message are changed) and reducing decoder complexity (i.e., avoid deblocking). In cases where not all block edges are equally relevant, the scaling function could modify only certain edges. On CRT displays, for instance, artifacts on vertical edges appear much more visible than on horizontal edges. Under such circumstances, reduced noise intensity should occur only on vertical edges  302  of pixel block  300 , as shown in  FIG. 5A . Under certain circumstance, the scaling function could modify only horizontal edges  402  of pixel block  400 , as illustrated in  FIG. 5B . 
     The foregoing describes a technique for simulating film grain in a coded image following decoding by scaling the film grain parameters to reduce complexity.