Method for processing image by using the mathematical model established based down sampling and interpolation
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A mathematical model and interpolation method technology, applied in the field of image processing, can solve the problem of keeping less information in images
Inactive Publication Date: 2008-05-28
HARBIN INST OF TECH
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[0006] The present invention proposes a method for processing images based on the establishment of a mathematical model based on downsampling and interpolation identity
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specific Embodiment approach 1
[0042] Specific embodiment one: illustrate this embodiment in conjunction with Fig. 1, the steps of this embodiment are as follows:
[0043] Step 1: Input the image F to be downsampled O ;
[0044] Step 2: Establish an interpolation mathematical model:
[0045] f H =C I (U H f L u V ), (1-1)
[0046] where F H Pixels equal to F O pixels, they have the same resolution, U H and U V An operator for interpolating zero pixels in the horizontal and vertical directions for low-resolution images; C I The operator for interpolation processing, that is, the pixel prediction model;
[0047] Step 3: Select the interpolation method, determine the pixel prediction model, that is, determine the operator C of the interpolation method I , while according to the image F O Size determination U H and U V ;
[0048] Step 4: Establish a downsampling mathematical model:
[0049] f L =D H (C F f O )D V , (1-2)
[0050] C F is the downsampling operator, that is, the pixel pred...
specific Embodiment approach 2
[0054] Embodiment 2: The difference between this embodiment and Embodiment 1 is that the interpolation methods selected in step 3 include the pixel copy interpolation method (PD), the bilinear interpolation method (Ave), and the edge-preserving image based on geometric duality. Interpolation method (GD), image interpolation method based on image grid triangulation (IMT) and local covariance method (EDILC); determine the pixel prediction model in it:
[0055] Y ^ ( n ) = F ( N ( Y ( n ) ) ) ; - - - ( 1 - 3 )
[0056] Among them, N(·) represents the neighborhood corresponding to Y(n) in X,...
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Abstract
The invention discloses an image processing method for establishing a mathematical model based on down sampling and interpolation, relates to an image processing method, and solves the prior problem that the image maintains a small amount of information after the down sampling. The invention adopts the steps that firstly, an image FO to be down-sampled is input; next, an interpolation mathematical model, namely, FH is equal to CI (U<H>F<L>U<V>) is established, and then an interpolation method is selected, a predictive model is determined, the arithmetic operator CI of the interpolation method is determined, and simultaneously UH and UV are determined according to the size of the image FO; and then a down sampling mathematical model, namely, FL is equal to DH (CF) DV is established; a predictive model with uniform image element of the interpolation and the down sampling is established, CF is obtained through the identity of the arithmetic operator the CI of the interpolation and the arithmetic operator the CF of the down sampling, and simultaneously the DH and the DV are obtained; finally, the down sampling processing to the image FO is performed through the obtained the FL being equal to the DH (CF) DV; the down sampling is obtained. The invention can be applied to the low code rate compression of images and videos, therefore reducing the amount of calculation of compression algorithm, quickening the processing speed and reducing the time delay, and also obviously improving the quality of restored images.
Description
technical field [0001] The invention relates to an image processing method, in particular to an image processing method in which image interpolation is applied in down-sampling. Background technique [0002] Scale transformation is a commonly used technique in image processing. Scale transformation includes scale reduction and scale promotion, which are completed by down-sampling and interpolation respectively. Image downsampling reduces the resolution of images and reduces the amount of processed data. It can be used as preprocessing for some applications in systems with limited conditions. It is also of great significance for low bit rate compression of images and videos. For example, the H.26X intra-frame compression process is similar to the classic static image compression algorithm JPEG, and JPEG is used as an object for description here. JPEG compression is known to cause annoying blockiness at low bitrates. However, if the same image is compressed by JPEG and then...
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