CN103345495A - Method for speedy presentation of ultra-precise image in network environment - Google Patents

Abstract

The invention provides a method for speedy presentation of an ultra-precise image in the network environment. The method for the speedy presentation of the ultra-precise image in the network environment comprises the following steps of carrying out X-stage sampling on a target high-precision image P0 according to the resolution ratio of the target high-precision image to obtain an image P1, an image P2, ..., and an image Px, wherein the resolution ratios of the image P1, the image P2, ..., and the image Px become smaller gradually, X>=1, and X is an integer; blocking is carried out on each image Pi of the image P0, on each image Pi of the image P1, on each image Pi of the image P2, ..., and on each image Pi of the image Px, and obtained blocks are saved in a transverse index saving mode, in a longitudinal index saving mode and in a recursion cross saving mode; when a request for presenting the image P0 with a pointed resolution ratio is received, a storage medium is searched, and an image Py with a resolution ratio closest to the pointed resolution ratio is selected; the image Py is then displayed on a screen. According to the method for the speedy presentation of the ultra-precise image in the network environment, due to the fact that the layering and blocking technique is adopted, the target image is saved from multiple dimensions, and therefore the required image can be read and presented fast and image browsing experience is improved for users.

Description

The very fast methods of exhibiting of super smart image under the network environment

Technical field

The invention belongs to the data display technical field, be specifically related to the very fast methods of exhibiting of super smart image under a kind of network environment.

Background technology

In recent years, along with improving constantly of computer hardware technique and making rapid progress of multimedia technology, by reading fast under this machine of computing machine or the network environment and showing that the demand of hyperfine imaged image also gets up more big.

Traditional image storage mode is: one dimension is stored whole image of hyperfine image, and, the resolution of whole the image of storing is highest resolution, therefore, be subjected to the restriction of the network bandwidth, calculator memory capacity and processing power, it is often very consuming time to client to download image from Website server, the result who causes thus is: when the user need browse certain pictures, need to wait for the long period, could show required picture fully on the display, therefore reduce user's viewing experience.

Summary of the invention

At the defective that prior art exists, the invention provides the very fast methods of exhibiting of super smart image under a kind of network environment, can read and show required image fast, thereby improve the experience of user's browse graph picture.

The technical solution used in the present invention is as follows:

The invention provides the very fast methods of exhibiting of super smart image under a kind of network environment, may further comprise the steps:

S1, setting the primary image unit R is the SxS pixel;

S2 carries out the sampling of x level to target with high precision image P0 by resolution, obtains image P1, image P2 that resolution is arranged by descending order ... image Px; Wherein, x 〉=1, x is integer;

S3 is to image P0, image P1, image P2 ... each pixel among the image Px is that the image Pi of aSxbS all carries out following operation: wherein, aS represents the product of a and S, and bS represents the product of b and S;

If a and b are integer, then image Pi is divided into the a*b shown in the formula 1 primary image unit;

$\left[\begin{array}{cccc}R11& R12& ...& R1a\\ R21& R22& ...& R2a\\ .& .& & .\\ .& .& & .\\ \mathrm{Rb}1& \mathrm{Rb}2& ...& \mathrm{Rba}\end{array}\right]$ Formula 1

If a and b are non-integer, then make a=[a]+1, b=[b]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit;

If a is non-integer, b is integer, then makes a=[a]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit;

If a is integer, b is non-integer, then makes b=[b]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit;

S4, in storage medium by horizontal a*b the primary image unit of index stores mode memory image Pi shown in the formula 2;

$\left[\begin{array}{cccc}R11& R12& ...& R1a\\ R21& R22& ...& R2a\\ .& .& & .\\ .& .& & .\\ \mathrm{Rb}1& \mathrm{Rb}2& ...& \mathrm{Rba}\end{array}\right]$ Formula 2

And/or in storage medium by vertical a*b the primary image unit of index stores mode memory image Pi shown in the formula 3;

$\left[\begin{array}{cccc}R11& R21& ...& \mathrm{Rb}1\\ R12& R22& ...& \mathrm{Rb}2\\ .& .& & .\\ .& .& & .\\ R1a& R2a& ...& \mathrm{Rba}\end{array}\right]$ Formula 3

And/or in storage medium, use a*b the primary image unit of recurrence interleaved mode memory image Pi;

S5, when receiving the image P0 that needs demonstration appointment resolution, the search storage medium is at image P0, image P1, image P2 ... choose the immediate image Py of resolution and described given resolution among the image Px; Then image Py is shown on the display screen; Carry out S6 then;

S6 judges whether the resolution of the described image Py that shows on the display screen is identical with described appointment resolution, if identical, process ends then; If inequality, then adjust the resolution of image Py, make the resolution of the image that obtains after the adjustment identical with described given resolution.

Preferably, S2 describedly carries out x level sampling to target with high precision image P0 by resolution, obtains image P1, image P2 that resolution is arranged by descending order ... image Px is specially:

If target with high precision image P0 is the MxN pixel, at first target with high precision image P0 is sampled, obtaining pixel is the image P1 of M/2xN/2;

Be that the image P1 of M/2xN/2 samples to pixel, obtaining pixel is the image P2 of M/4xN/4;

Be that the image P2 of M/4xN/4 samples to pixel, obtaining pixel is the image P3 of M/8xN/8;

The rest may be inferred, till the pixel of resulting image Px only comprises a described primary image unit R.

Preferably, after the S4, also comprise:

Set up the multi-dimensional indexing storage organization; Be specially: according to shown in the formula 2 laterally the index stores structure store a*b the primary image unit of each image Pi into server end; And, according to shown in the formula 3 vertically the index stores structure store a*b the primary image unit of each image Pi into server end; And, store a*b the primary image unit of each image Pi into server end according to recurrence interleaved structure;

Client is to the browse request message of described server end transmission to image P0; Wherein, carry the local region-of-interest parameter of image P0 in the described browse request message;

Described server end is resolved described browse request message, obtains the local region-of-interest parameter of described image P0; Then, by searching described multi-dimensional indexing storage organization, read fast at least one the specific primary image unit that comprises local region-of-interest;

Described server end returns described specific primary image unit to described client;

Described client shows described specific primary image unit.

Preferably, described local region-of-interest parameter comprises one or more in the display window size information of the centre coordinate information of the size information of the positional information of the resolution information of local region-of-interest, local region-of-interest, local region-of-interest, local region-of-interest and local region-of-interest.

Beneficial effect of the present invention is as follows:

The very fast methods of exhibiting of super smart image under the network environment provided by the invention owing to adopt the hierarchical block technology, from a plurality of dimensions storage target images, therefore, can read fast and shows required image, thereby improve the experience of user's browsing pictures.

Description of drawings

Fig. 1 is the very fast methods of exhibiting schematic flow sheet of super smart image under the network environment provided by the invention.

Embodiment

The present invention is described in detail below in conjunction with accompanying drawing:

As shown in Figure 1, the invention provides the very fast methods of exhibiting of super smart image under a kind of network environment, may further comprise the steps:

S1, setting the primary image unit R is the SxS pixel;

S2 carries out the sampling of x level to target with high precision image P0 by resolution, obtains image P1, image P2 that resolution is arranged by descending order ... image Px; Wherein, x 〉=1, x is integer;

The present invention does not limit concrete sample mode, as a kind of preferred embodiment, can take following sample mode: as shown in table 1, establishing target with high precision image P0 is the MxN pixel, at first target with high precision image P0 is sampled, obtaining pixel is the image P1 of M/2xN/2;

Be that the image P1 of M/2xN/2 samples to pixel, obtaining pixel is the image P2 of M/4xN/4;

Be that the image P2 of M/4xN/4 samples to pixel, obtaining pixel is the image P3 of M/8xN/8;

The rest may be inferred, till the pixel of resulting image Px only comprises a primary image unit R.

Table 1

S3 is to image P0, image P1, image P2 ... each pixel among the image Px is that the image Pi of aSxbS all carries out following operation: wherein, aS represents the product of a and S, and bS represents the product of b and S;

If a and b are integer, then image Pi is divided into the a*b shown in the formula 1 primary image unit; Comprise a*b primary image unit in the formula 1 altogether, the pixel of each primary image unit is the SxS pixel.For example: be 7 if a is 10, b, then image Pi be divided into 70 primary image unit;

$\left[\begin{array}{cccc}R11& R12& ...& R1a\\ R21& R22& ...& R2a\\ .& .& & .\\ .& .& & .\\ \mathrm{Rb}1& \mathrm{Rb}2& ...& \mathrm{Rba}\end{array}\right]$ Formula 1

If a and b are non-integer, then make a=[a]+1, b=[b]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit; Wherein, a=[a]+1 implication is: a round numbers adds 1 value again and composes to a, for example, if image Pi pixel is 10.2S x 7.8S, then replenish blank pixel in image Pi, obtaining pixel is the new images Pi of 11Sx8S, then new images Pi is divided into the 11*8 shown in the formula 1 primary image unit.

If a is non-integer, b is integer, then makes a=[a]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit;

If a is integer, b is non-integer, then makes b=[b]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit;

S4, in storage medium by horizontal a*b the primary image unit of index stores mode memory image Pi shown in the formula 2;

$\left[\begin{array}{cccc}R11& R12& ...& R1a\\ R21& R22& ...& R2a\\ .& .& & .\\ .& .& & .\\ \mathrm{Rb}1& \mathrm{Rb}2& ...& \mathrm{Rba}\end{array}\right]$ Formula 2

And/or in storage medium by vertical a*b the primary image unit of index stores mode memory image Pi shown in the formula 3;

$\left[\begin{array}{cccc}R11& R21& ...& \mathrm{Rb}1\\ R12& R22& ...& \mathrm{Rb}2\\ .& .& & .\\ .& .& & .\\ R1a& R2a& ...& \mathrm{Rba}\end{array}\right]$ Formula 3

And/or in storage medium, use a*b the primary image unit of recurrence interleaved mode memory image Pi;

Above-mentioned S1-S4 has realized employing hierarchical block technology, from the process of a plurality of dimension storage target images.This kind storage mode can abbreviate knowledge cloud atlas storage format as.After image adopts knowledge cloud atlas storage format, adopt following method to read and the exploded view picture, can read and show required image fast.Concrete, the present invention introduces two kinds of image shows processes:

(1) first kind of image shows process is S5-S6:

S5, when receiving the image P0 that needs demonstration appointment resolution, the search storage medium is at image P0, image P1, image P2 ... choose the immediate image Py of resolution and described given resolution among the image Px; Then image Py is shown on the display screen; Carry out S6 then;

S6 judges whether the resolution of the described image Py that shows on the display screen is identical with described appointment resolution, if identical, process ends then; If inequality, then adjust the resolution of image Py, make the resolution of the image that obtains after the adjustment identical with described given resolution.

By knowledge cloud atlas storage format, can read fast and the immediate image of given resolution, only need fine setting then, the image resolution ratio of displaying is met the requirements.Therefore, improved that image reads and displaying speed.

(2) second kinds of image shows processes:

Set up the multi-dimensional indexing storage organization; Be specially: according to shown in the formula 2 laterally the index stores structure store a*b the primary image unit of each image Pi into server end; And, according to shown in the formula 3 vertically the index stores structure store a*b the primary image unit of each image Pi into server end; And, store a*b the primary image unit of each image Pi into server end according to recurrence interleaved structure;

Client is to the browse request message of described server end transmission to image P0; Wherein, carry the local region-of-interest parameter of image P0 in the described browse request message; Wherein, local region-of-interest parameter comprises one or more in the display window size information of the centre coordinate information of the size information of the positional information of the resolution information of local region-of-interest, local region-of-interest, local region-of-interest, local region-of-interest and local region-of-interest.

Described server end is resolved described browse request message, obtains the local region-of-interest parameter of described image P0; Then, by searching described multi-dimensional indexing storage organization, read fast at least one the specific primary image unit that comprises local region-of-interest;

Described server end returns described specific primary image unit to described client;

Described client shows described specific primary image unit.

In sum, the very fast methods of exhibiting of super smart image under the network environment provided by the invention is owing to adopt the hierarchical block technology, from a plurality of dimension storage target images, therefore, can read fast and show required image, thereby improve the experience of user's browsing pictures.

The above only is preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the principle of the invention; can also make some improvements and modifications, these improvements and modifications also should be looked protection scope of the present invention.

Claims (4)

1. the very fast methods of exhibiting of super smart image under the network environment is characterized in that, may further comprise the steps:

S1, setting the primary image unit R is the SxS pixel;

S2 carries out the sampling of x level to target with high precision image P0 by resolution, obtains image P1, image P2 that resolution is arranged by descending order ... image Px; Wherein, x 〉=1, x is integer;

S3 is to image P0, image P1, image P2 ... each pixel among the image Px is that the image Pi of aSxbS all carries out following operation: wherein, aS represents the product of a and S, and bS represents the product of b and S;

If a and b are integer, then image Pi is divided into the a*b shown in the formula 1 primary image unit;

$\left[\begin{array}{cccc}R11& R12& ...& R1a\\ R21& R22& ...& R2a\\ .& .& & .\\ .& .& & .\\ \mathrm{Rb}1& \mathrm{Rb}2& ...& \mathrm{Rba}\end{array}\right]$ Formula 1

If a and b are non-integer, then make a=[a]+1, b=[b]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit;

If a is non-integer, b is integer, then makes a=[a]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit;

If a is integer, b is non-integer, then makes b=[b]+1, in image Pi, replenish blank pixel then, obtaining pixel is the new images Pi of aSxbS, then new images Pi is divided into the a*b shown in the formula 1 primary image unit;

S4, in storage medium by horizontal a*b the primary image unit of index stores mode memory image Pi shown in the formula 2;

$\left[\begin{array}{cccc}R11& R12& ...& R1a\\ R21& R22& ...& R2a\\ .& .& & .\\ .& .& & .\\ \mathrm{Rb}1& \mathrm{Rb}2& ...& \mathrm{Rba}\end{array}\right]$ Formula 2

And/or in storage medium by vertical a*b the primary image unit of index stores mode memory image Pi shown in the formula 3;

$\left[\begin{array}{cccc}R11& R21& ...& \mathrm{Rb}1\\ R12& R22& ...& \mathrm{Rb}2\\ .& .& & .\\ .& .& & .\\ R1a& R2a& ...& \mathrm{Rba}\end{array}\right]$ Formula 3

And/or in storage medium, use a*b the primary image unit of recurrence interleaved mode memory image Pi;

S5, when receiving the image P0 that needs demonstration appointment resolution, the search storage medium is at image P0, image P1, image P2 ... choose the immediate image Py of resolution and described given resolution among the image Px; Then image Py is shown on the display screen; Carry out S6 then;

S6 judges whether the resolution of the described image Py that shows on the display screen is identical with described appointment resolution, if identical, process ends then; If inequality, then adjust the resolution of image Py, make the resolution of the image that obtains after the adjustment identical with described given resolution.

2. the very fast methods of exhibiting of super smart image under the network environment according to claim 1, it is characterized in that S2 describedly carries out x level sampling to target with high precision image P0 by resolution, obtain image P1, image P2 that resolution is arranged by descending order ... image Px is specially:

If target with high precision image P0 is the MxN pixel, at first target with high precision image P0 is sampled, obtaining pixel is the image P1 of M/2xN/2;

Be that the image P1 of M/2xN/2 samples to pixel, obtaining pixel is the image P2 of M/4xN/4;

Be that the image P2 of M/4xN/4 samples to pixel, obtaining pixel is the image P3 of M/8xN/8;

The rest may be inferred, till the pixel of resulting image Px only comprises a described primary image unit R.

3. the very fast methods of exhibiting of super smart image under the network environment according to claim 1 is characterized in that, after the S4, also comprises:

Set up the multi-dimensional indexing storage organization; Be specially: according to shown in the formula 2 laterally the index stores structure store a*b the primary image unit of each image Pi into server end; And, according to shown in the formula 3 vertically the index stores structure store a*b the primary image unit of each image Pi into server end; And, store a*b the primary image unit of each image Pi into server end according to recurrence interleaved structure;

Client is to the browse request message of described server end transmission to image P0; Wherein, carry the local region-of-interest parameter of image P0 in the described browse request message;

Described server end is resolved described browse request message, obtains the local region-of-interest parameter of described image P0; Then, by searching described multi-dimensional indexing storage organization, read fast at least one the specific primary image unit that comprises local region-of-interest;

Described server end returns described specific primary image unit to described client;

Described client shows described specific primary image unit.

4. the very fast methods of exhibiting of super smart image under the network environment according to claim 3, it is characterized in that described local region-of-interest parameter comprises one or more in the display window size information of the centre coordinate information of the size information of the positional information of the resolution information of local region-of-interest, local region-of-interest, local region-of-interest, local region-of-interest and local region-of-interest.

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