CN110113618B

CN110113618B - Image storage method, reading method, storage device and reading device

Info

Publication number: CN110113618B
Application number: CN201910503132.9A
Authority: CN
Inventors: 吴婷婷; 侯强波; 蔡晓辉; 杨平
Original assignee: Suzhou Synbio Technologies Co ltd
Current assignee: Suzhou Synbio Technologies Co ltd
Priority date: 2019-06-11
Filing date: 2019-06-11
Publication date: 2021-09-03
Anticipated expiration: 2039-06-11
Also published as: WO2020248488A1; CN110113618A

Abstract

The present disclosure relates to the field of information processing technologies, and in particular, to an image storage method, an image reading method, an image storage device, and an image reading device. The method comprises the following steps: performing wavelet transformation on the original image to obtain wavelet transformation coefficients corresponding to the multilevel subimages; acquiring a target wavelet transformation coefficient corresponding to a sub-image with the level greater than or equal to a preset value; and coding the target wavelet transform coefficient into a DNA sequence according to the preset corresponding relation between the DNA base sequence and the wavelet transform coefficient. According to the method, the target wavelet transform coefficient corresponding to the sub-image meeting the requirements is selected for DNA coding according to the importance of the level and the type of the sub-image on image reconstruction and the data volume of the sub-image, the coded data volume can be effectively compressed, high-definition decoding can be guaranteed, and efficient storage of image data is realized.

Description

Image storage method, reading method, storage device and reading device

Technical Field

The present disclosure relates to the field of information processing technologies, and in particular, to an image storage method, an image reading method, an image storage device, and an image reading device.

Background

With the development of life science technology and the cross development of life science and other scientific technology, it is possible to use genetic material deoxyribonucleic acid (DNA) as a storage medium. The development of DNA synthesis and sequencing technology has provided technical support for its use as a numerical storage vehicle. The storage of digital information DNA refers to the storage of digital information in the base sequence of DNA, and this technique artificially synthesizes DNA for storage using a DNA synthesizer and reads the stored information using a DNA sequencer. Compared with the existing tape or hard disk storage medium, the DNA serving as the storage medium has the following advantages: firstly, the volume of DNA is extremely small, one base pair is only dozens of atoms, the DNA is taken as a storage medium, and the volume of the whole data is far smaller than that of a traditional optical disk or hard disk; secondly, the DNA density is high, 1 g of DNA is smaller than the size of a drop of dew on a fingertip, and 700TB data can be stored, which is equivalent to 1.4 ten thousand blue-ray discs with the capacity of 50GB or 233 hard discs with the capacity of 3TB, and the latter is about 151 kg; and the DNA has extremely strong stability and can be stored for a long time.

In the related art, in 8 months 2012, a DNA sequence capable of storing 96 bits of data was synthesized by harvard team led by George Church and sriram korsuri. In a specific storage method, binary values are assigned to the constituent bases adenine (a), guanine (G), cytosine (C), and thymine (T) of DNA, respectively, and DNA sequences are synthesized by a microfluidic chip so that the positions of the sequences match a relevant data set. When data needs to be read, only the DNA sequence needs to be reduced to binary. The direct storage of data using DNA as a storage medium results in low information compression rate and large amount of encoded synthesis, which is not favorable for practical application.

With the development of the internet, the demand of people for high-definition images is increasing. Especially in some special application fields, such as video surveillance, medical images, etc., the storage requirement for the image data amount is very large, and the conventional storage method will result in a large storage cost, such as 700TB data mentioned above, and 1.4 ten thousand blu-ray discs with a capacity of 50GB or 233 hard discs with a capacity of 3TB, which is about 151 kg. Therefore, efficient storage of images is a technical problem that needs to be solved urgently.

Disclosure of Invention

To overcome the problems in the related art, the present disclosure provides an image storage method, a reading method, a storage device, and a reading device.

According to a first aspect of embodiments of the present disclosure, there is provided an image storage method, including:

performing wavelet transformation on the original image to obtain wavelet transformation coefficients corresponding to the multilevel subimages;

acquiring a target wavelet transformation coefficient corresponding to a sub-image with the level greater than or equal to a preset value;

and coding the target wavelet transform coefficient into a DNA sequence according to the preset corresponding relation between the DNA base sequence and the wavelet transform coefficient.

In a possible implementation manner, after acquiring the target wavelet transform coefficient corresponding to the sub-image with the level greater than or equal to the preset value, the method further includes:

acquiring pixel information of the sub-image, wherein the pixel information comprises pixel brightness, pixel chroma and pixel saturation;

and adjusting the wavelet transformation coefficient of the sub-image so that the adjusted wavelet transformation coefficient is matched with the pixel information of the sub-image.

In one possible implementation manner, the encoding the target wavelet transform coefficient into a DNA sequence according to a preset correspondence between a DNA base sequence and the wavelet transform coefficient includes:

acquiring the sign and the value of the wavelet transform coefficient;

and respectively coding the signs and the numerical values of the wavelet transform coefficients into DNA sequences according to the corresponding relation between the DNA base sequences and the signs and the corresponding relation between the DNA base sequences and the numerical values.

In a possible implementation manner, the encoding the target wavelet transform coefficient into a DNA sequence according to a preset correspondence between a DNA base sequence and the wavelet transform coefficient further includes:

if there are consecutive N identical numbers in the values, (N ≧ 2), the wavelet transform coefficients are encoded into a DNA sequence according to the following format: "marker + DNA base sequence corresponding to numerical value N".

In one possible implementation manner, after encoding the target wavelet transform coefficient into a DNA sequence according to a preset correspondence between a DNA base sequence and the wavelet transform coefficient, the method includes:

marking a row number for a DNA base sequence corresponding to the target wavelet transform coefficient according to the position of the target wavelet transform coefficient in the sub-image;

cutting the DNA base sequence of the same row number according to a preset length value to obtain an X segment of DNA fragment (X is more than or equal to 1);

adding a base sequence corresponding to an index mark to the DNA fragment, wherein the index mark comprises the grade of the sub-image corresponding to the DNA fragment, the pixel information of the sub-image corresponding to the DNA fragment, the type of the sub-image corresponding to the DNA fragment, and the line number and the segment number of the DNA fragment.

In one possible implementation, the adding the base sequence corresponding to the index marker to the DNA fragment includes:

and adding base sequences corresponding to the index markers to the front and back ends of the DNA fragment.

In one possible implementation, the DNA base sequence includes at least one of natural base a, base G, base T, and base C, and synthetic base Z, base P, base S, and base B.

According to a second aspect of the embodiments of the present disclosure, there is provided an image reading method including:

extracting a DNA sequence corresponding to the subimage according to the coding DNA sequence of the original image;

determining a wavelet transformation coefficient corresponding to the pixel data of the sub-image according to the DNA sequence corresponding to the sub-image and the corresponding relation between the DNA base sequence and the wavelet transformation coefficient;

and performing inverse wavelet transform processing on the wavelet transform coefficient to obtain a decoded image of the original image.

According to a third aspect of the embodiments of the present disclosure, there is provided an image storage apparatus including:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform the storing method described in any of the embodiments of the present disclosure.

According to a fourth aspect of the embodiments of the present disclosure, there is provided an image reading apparatus comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform the reading method according to any one of the embodiments of the present disclosure.

According to a fifth aspect of embodiments of the present disclosure, there is provided a non-transitory computer-readable storage medium, wherein instructions of the storage medium, when executed by a processor, enable the processor to perform a storage method according to any one of the embodiments of the present disclosure.

According to a sixth aspect of embodiments of the present disclosure, there is provided a non-transitory computer-readable storage medium, wherein instructions of the storage medium, when executed by a processor, enable the processor to perform a reading method according to any one of the embodiments of the present disclosure.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects: according to the method, the wavelet transform function is utilized to perform wavelet transform on the original image to obtain sub-images of different levels and different types (the different types comprise low-frequency components, horizontal-direction components, vertical-direction components and diagonal-direction components), and according to the importance of the levels and types of the sub-images on image reconstruction and the data volume of the sub-images, a target wavelet transform coefficient corresponding to the sub-images meeting requirements is selected to perform DNA coding, so that the stored data volume can be effectively compressed, high-definition decoding can be guaranteed, and efficient storage of image data can be realized. In the embodiment of the disclosure, the decimal wavelet transform coefficient is preferred, so that the probability of continuous occurrence of bases can be reduced, the synthesis difficulty of DNA is reduced, and effective coding and storage are ensured.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.

FIG. 1 is a flow chart illustrating an image storage method according to an exemplary embodiment.

FIG. 2 is a diagram illustrating a one-level decomposition of an image, according to an example embodiment.

FIG. 3 is a three-level exploded schematic diagram of an image shown in accordance with an exemplary embodiment.

FIG. 4 is a flow chart illustrating an image storage method according to an exemplary embodiment.

FIG. 5 is a flow chart illustrating an image storage method according to an exemplary embodiment.

FIG. 6 is a flow chart illustrating an image storage method according to an exemplary embodiment.

FIG. 7 is a flow chart illustrating an image storage method according to an exemplary embodiment.

FIG. 8 is a flow chart illustrating an image storage method according to an exemplary embodiment.

Fig. 9 is a flowchart illustrating an image reading method according to an exemplary embodiment.

Fig. 10 is a block diagram illustrating an image storage apparatus according to an exemplary embodiment, and fig. 10 is a block diagram similarly applicable to an image reading apparatus.

Fig. 11 is a block diagram illustrating an image storage apparatus according to an exemplary embodiment, and fig. 11 is a block diagram similarly applicable to an image reading apparatus.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

In order to facilitate those skilled in the art to understand the technical solutions provided by the embodiments of the present disclosure, a technical environment for implementing the technical solutions is described below.

The DNA is used as a storage medium, has the advantages of small volume, high density and long-term storage, and can be used as a new medium for future data storage. In multimedia files, images occupy an important part, particularly with the development of the internet, the demand of people for high-definition images is increased, the data volume of the images is also increased, binary data corresponding to the images are directly coded into DNA sequences, a large number of nucleic acid sequences are generated, the workload is large, base sequences corresponding to the binary data are repeated continuously for many times, the DNA synthesis failure is easily caused, and the difficulty is increased for image storage.

Based on the practical technical requirements similar to those described above, it is necessary to perform reasonable data compression processing before image storage and design effective encoding rules so that images can be encoded and stored efficiently and accurately.

The data processing method according to the present disclosure is described in detail below with reference to fig. 1. Fig. 1 is a flowchart of an image storage method according to an embodiment of the present disclosure. Although the present disclosure provides method steps as illustrated in the following examples or figures, more or fewer steps may be included in the method based on conventional or non-inventive efforts. In steps where no necessary causal relationship exists logically, the order of execution of the steps is not limited to that provided by the disclosed embodiments.

Specifically, as shown in fig. 1, an embodiment of an image storage provided by the present disclosure may be applied to an image storage using genetic material DNA as a storage medium, where the image format includes, but is not limited to, BMP format, JPEG format, GIF format, PSD format, PNG format, and TIFF format, and may be applied to color pictures and black and white pictures. The method comprises the following steps:

in step S11, the original image is subjected to wavelet transform to obtain wavelet transform coefficients corresponding to the multilevel sub-images.

In the embodiment of the present disclosure, the performing wavelet transform on the original image includes performing wavelet transform on pixel data of the original image by using a wavelet transform function to obtain a wavelet transform coefficient corresponding to a multi-level sub-image. Specifically, in one example, the original image may be wavelet transformed using a Mallat pyramid decomposition algorithm in wavelet transformation: for an image with m rows and n columns, the Mallat pyramid decomposition algorithm wavelet transform process is, as shown in fig. 2, to perform one-dimensional wavelet transform on each row of the image to obtain a low-frequency coefficient L1 and a high-frequency coefficient H1, and then perform one-dimensional wavelet transform on each column of the obtained LH image (the size of which is still m rows and n columns), so that the image after the one-level wavelet transform can be divided into four parts, i.e., LL1, HL1, LH1, and HH1, where LL1 is a one-level low-frequency sub-image, HL1 is a one-level high-frequency horizontal sub-image, LH1 is a one-level high-frequency vertical sub-image, and HH1 is a one-level high-frequency diagonal sub-image. Referring to fig. 3, two-dimensional wavelet transform of two, three, or even higher levels is performed by one more wavelet transform on the lower frequency sub-image LL1 portion of the wavelet transform image of the previous level. In fig. 3, 1, 2, and 3 denote the number of levels of decomposition, i.e., the level of the sub-image, L denotes a low-frequency coefficient, and H denotes a high-frequency coefficient.

In step S12, the target wavelet transform coefficients corresponding to the sub-images having the level greater than or equal to the preset value are acquired.

In the embodiment of the present disclosure, after performing a multi-level wavelet transform on an original image by using a wavelet transform function, sub-images of corresponding levels are obtained, the resolution of the sub-images of the same type and different levels is different, and in an N-level wavelet transform, the resolution of the sub-image with a higher decomposition level is lower, for example, referring to fig. 3, in a structural diagram of a three-level wavelet transform image, the frequency of the two-level sub-images HL2, LH2, HH2 is lower than the resolution of the one-level sub-images HL1, LH1, HH 1. Therefore, in the embodiment of the present disclosure, according to actual requirements, the target wavelet transform coefficient corresponding to the sub-image with the level greater than or equal to the preset value may be obtained, and the wavelet transform coefficient corresponding to the sub-image with the level less than the preset value may be discarded and not used, so as to implement compression of the stored data amount. On this basis, the embodiment of the present disclosure may use, but is not limited to, a thresholding method to further compress the target wavelet transform coefficients, for example, for sub-images of the same level, all wavelet transform coefficients corresponding to low-frequency sub-images are retained, waiting for subsequent storage, and then selecting a global threshold to process high-frequency coefficients of each level, or processing high-frequency coefficients of different levels with different thresholds, setting the high-frequency coefficient whose absolute value is lower than the threshold to 0, and otherwise retaining the high-frequency coefficient. And image reconstruction is carried out by using the reserved non-zero wavelet coefficients.

In step S13, the target wavelet transform coefficient is stored as a DNA sequence according to a preset correspondence between the DNA base sequence and the wavelet transform coefficient.

In the embodiment of the present disclosure, the preset corresponding relationship between the DNA base sequence and the wavelet transform coefficient includes a one-to-one corresponding relationship, as shown in table 1, table 1 lists the case that the wavelet transform coefficient is at most two digits, in practical applications, the wavelet transform corresponding to each sub-image may include two or more digits of values, in one example, a rounding method may be adopted to retain the wavelet coefficients with two or more digits of values to two significant values, and a configuration may also be made such that a plurality of consecutive low-digit values correspond to the same base sequence, and more corresponding relationships between the DNA base sequence and the wavelet transform coefficient, which is not limited herein.

In one possible implementation manner, for convenience of storage, the target wavelet transform coefficient is subjected to a decimal processing, that is, a maximum absolute value (i.e., an absolute value of a coefficient having a maximum absolute value) of the target wavelet transform coefficient corresponding to the sub-image is selected, and the target wavelet transform coefficient corresponding to the sub-image is divided by the maximum absolute value to obtain an intermediate value, where the intermediate value falls within a range of [ -1,1 ]. When the image is decoded, the target wavelet transform coefficient can be obtained by multiplying the intermediate value by the maximum absolute value.

In the embodiment of the present disclosure, the value of the wavelet transform coefficient may include binary and above binary numbers such as: ternary number, octal number, decimal number, etc., the numerical representation of the wavelet transform coefficients is that the larger the binary number is, the fewer the times of appearance of the same base sequence is, for example, the binary number represents the wavelet transform coefficient, such as "010101010101", according to some corresponding rule: 00 corresponds to A, 01 corresponds to T,10 corresponds to C, 11 corresponds to G, the binary number is represented as TTTTTT, difficulty is caused to gene synthesis, errors are easy to occur, and therefore the wavelet transformation coefficient selected from high-level system representation is superior to low-level system representation.

The embodiment of the present disclosure considers that, unlike general data, each pixel value of image data has a high correlation with surrounding neighboring pixels, and therefore, an original image may be compressed by using a wavelet transform method, which reduces the amount of data to be stored. In consideration of the limitation of the traditional storage medium, the image data needs to be converted into a binary form for storage, the number of storage bits is large, the occupied space is large, the DNA storage medium is adopted in the embodiment of the disclosure, the image data does not need to be converted into the binary form, and the corresponding relation between the decimal storage data and the DNA base sequence is established, so that the number of storage bits is greatly reduced, and the storage synthesis amount is further reduced.

TABLE 1 Table of correspondence between numbers and DNA base sequences

Number of	DNA	Number of	DNA	Number of	DNA	Number of	DNA	Number of	DNA
										0	A	20	CP	40	BA	60	ZP	80	ACA
1	T	21	CS	41	BT	61	ZS	81	ACT
										2	C	22	CB	42	BC	62	ZB	82	ACC
3	G	23	CZ	43	BG	63	ZZ	83	ACG
										4	B	24	GA	44	BP	64	SA	84	ACP
5	P	25	GT	45	BS	65	ST	85	ACS
										6	Z	26	GC	46	BB	66	SC	86	ACB
7	S	27	GG	47	BZ	67	SG	87	ACZ
										8	AA	28	GP	48	PA	68	SP	88	AGA
9	AT	29	GS	49	PT	69	SS	89	AGT
										10	AC	30	GB	50	PC	70	SB	90	AGC
11	AG	31	GZ	51	PG	71	SZ	91	AGG
										12	AP	32	TA	52	PP	72	AAA	92	AGP
13	AS	33	TT	53	PS	73	AAT	93	AGS
										14	AB	34	TC	54	PB	74	AAC	94	AGB
15	AZ	35	TG	55	PZ	75	AAG	95	AGZ
										16	CA	36	TP	56	ZA	76	AAP	96	ABG
17	CT	37	TS	57	ZT	77	AAB	97	ABP
										18	CC	38	TB	58	ZC	78	AAZ	98	ABS
19	CG	39	TZ	59	ZG	79	ACA	99	ABZ

Note: the integer "1" is denoted by "TGATP", and the integer "-1", i.e. "TCATP"

According to the method, the wavelet transform function is utilized to perform wavelet transform on the original image to obtain sub-images of different levels and different types (the different types comprise low-frequency components, horizontal-direction components, vertical-direction components and diagonal-direction components), and according to the importance of the levels and types of the sub-images on image reconstruction and the data volume of the sub-images, a target wavelet transform coefficient corresponding to the sub-images meeting requirements is selected to perform DNA storage, so that the stored data volume can be effectively compressed, high-definition decoding can be guaranteed, and efficient storage of image data can be realized. In the embodiment of the disclosure, the decimal wavelet transform coefficient is preferred, so that the probability of continuous occurrence of bases can be reduced, the synthesis difficulty of DNA is reduced, and effective coding and storage are ensured.

Fig. 4 is a flowchart illustrating an image storing method according to an exemplary embodiment, and further includes step S14 and step S15 after the step S12, as shown in fig. 2.

In step S14, acquiring pixel information of the sub-image, where the pixel information includes pixel brightness, pixel chromaticity, and pixel saturation;

in step S15, the wavelet transform coefficients of the sub-image are adjusted so that the wavelet transform coefficients after adjustment match the pixel information of the sub-image.

In the embodiment of the present disclosure, the pixel information of the sub-image may be acquired as follows: acquiring matrix data of an RGB color space of an original image, wherein the value range of each point value of the matrix data comprises 0-255, converting the RGB data through a formula (1), a formula (2) and a formula (3), so that data compression of the original image can be realized, and YUV color data of the original image is obtained, wherein the formula (1), the formula (2) and the formula (3) comprise:

Y＝0.299R+0.587G+0.114B (1)

U＝-01687R-0.3313G+0.5B (2)

V＝0.5R-0.4187G-0.0813B (3)

wherein Y represents brightness, i.e., a gray scale value; and U represents the chroma and V represents the saturation, which is used to describe the color and saturation of the image for specifying the color of the pixel.

The pixel information of the sub-image can be described by YUV, and the corresponding wavelet transform coefficients of the sub-image are also distinguished by Y, U, V, that is, the wavelet transform coefficients corresponding to the sub-image include Y-type wavelet transform coefficients, U-type wavelet transform coefficients and V-type wavelet transform coefficients. Since different pixel information has different meanings for image reconstruction, the wavelet transform coefficients of the sub-image are adjusted so that the adjusted wavelet transform coefficients match the pixel information of the sub-image. For example: carrying out five-level wavelet transform on an original image to obtain a sub-image with the highest level being five levels, coding the sub-image with the levels of three or more, and coding Y-type wavelet transform coefficients corresponding to the selected three-level sub-image, four-level sub-image and five-level sub-image according to the pixel information of the sub-image, if the pixel information is brightness Y; if the pixel information is the chroma U and the saturation V, the U-shaped wavelet transform coefficient and the V-shaped wavelet transform coefficient corresponding to the five-level sub-image are coded, and the U-shaped wavelet transform coefficient and the V-shaped wavelet transform coefficient corresponding to the four-level sub-image and the three-level sub-image are not coded any more.

In the embodiment of the present disclosure, considering that different types of pixel information have different meanings for image reconstruction, the luminance information Y with a strong image reconstruction effect may be encoded with more levels of sub-images according to actual requirements, and correspondingly, the chrominance U or the saturation V with a weak image reconstruction effect may be encoded with fewer levels of sub-images, so that the amount of stored data of the image may be further compressed effectively and reasonably.

Fig. 5 is a flowchart illustrating an image storing method according to an exemplary embodiment, and as shown in fig. 5, the step S13 includes steps 131 and 132:

in step S131, the sign and the value of the wavelet transform coefficient are acquired.

In step S132, the sign and the numerical value of the wavelet transform coefficient are encoded into a DNA sequence based on the correspondence between the DNA base sequence and the sign and the correspondence between the DNA base sequence and the numerical value, respectively.

In the embodiment of the disclosure, the wavelet transform coefficients corresponding to the sub-images obtained by the original image through wavelet transform have a fraction of positive number and negative number, and the sign includes a positive sign and a sign. The correspondence of the DNA base sequence to the symbol, in one example, when the effective numerical value is a positive number, the corresponding base sequence may set "TG"; when the effective numerical value is a negative number, the corresponding base sequence may be set to "TC". The correspondence relationship between the DNA base sequences and the numerical values may include any one of the above examples, and the DNA base sequences and the numerical values shown in Table 1 are in one-to-one correspondence relationship. By establishing the corresponding relation between the DNA base sequence and the symbol, the embodiment of the disclosure can only need to mark and distinguish through the base sequence corresponding to the symbol when the effective numerical parts are the same and the signs are different, so that the same numerical parts can share one set of corresponding relation, and the coding complexity is reduced.

The data processing method according to the present disclosure is described in detail below with reference to fig. 6. FIG. 6 is a method flow diagram of one embodiment of an image storage method provided by the present disclosure. Although the present disclosure provides method steps as illustrated in the following examples or figures, more or fewer steps may be included in the method based on conventional or non-inventive efforts. In steps where no necessary causal relationship exists logically, the order of execution of the steps is not limited to that provided by the disclosed embodiments.

Specifically, as shown in fig. 6, the step S13 further includes a step S133:

in step S133, if N consecutive identical numbers of the values occur, (N.gtoreq.2), the wavelet transform coefficients are encoded into a DNA sequence according to the following format: "marker + DNA base sequence corresponding to numerical value N".

In the embodiment of the present disclosure, the same number appears N times in succession in the synthesized DNA sequence, for example, in the high-level wavelet coefficient, the probability of appearing zero is high, and the continuous coding of the same DNA base sequence causes difficulty in synthesis and redundancy in coding, so that the following format "tag + DNA base sequence corresponding to the number N" can be used for coding. For example, the marker "APA" represents "0 s", and the wavelet coefficient "0000000000" may be represented as "APA + AC", i.e., "APAAC". In the embodiment of the present disclosure, if N consecutive identical numbers of the values occur, (N ≧ 2), the wavelet transform coefficient is encoded into a DNA sequence according to the following format: the DNA base sequence corresponding to the marker plus the numerical value N can greatly reduce the number of synthesized DNA and realize effective data compression.

The data processing method according to the present disclosure is described in detail below with reference to fig. 7. FIG. 7 is a method flow diagram of one embodiment of an image storage method provided by the present disclosure. Although the present disclosure provides method steps as illustrated in the following examples or figures, more or fewer steps may be included in the method based on conventional or non-inventive efforts. In steps where no necessary causal relationship exists logically, the order of execution of the steps is not limited to that provided by the disclosed embodiments.

Specifically, as shown in fig. 7, an embodiment of an image storage provided by the present disclosure further includes, after the step S13, a step S16, a step S17, and a step S18:

in step S16, marking a row number for the DNA base sequence corresponding to the target wavelet transform coefficient according to the position of the target wavelet transform coefficient in the sub-image to which the target wavelet transform coefficient belongs;

in the embodiment of the present disclosure, in order to express the property of the encoded DNA sequence and facilitate decoding, the target wavelet transform coefficients corresponding to the encoded sub-images are further processed, that is, the DNA base sequences corresponding to the target wavelet transform coefficients in the same row of the sub-images are marked with row numbers, in one example, a continuous numbering mode may be adopted, for example, for three-level high-frequency horizontal sub-images, the size of the coefficient matrix of the wavelet transform is 650 × 480, and for the DNA sequence encoded by the 480 wavelet transform coefficients in the first row, the row number is marked with 1; the 480 wavelet transform coefficients of the second row encode DNA sequences, row number label 2; by analogy, there are 650 rows with a maximum row number of 650.

In step S17, the DNA base sequence of the same line number is cut according to a preset length value to obtain X segments of DNA fragments (X is more than or equal to 1).

In the embodiment of the present disclosure, in order to synthesize a DNA sequence efficiently, the DNA base sequence of the same row number is cut according to a preset length value, for example, 150nt, to obtain X DNA fragments. The selection of the preset length value and the preset width value is not limited according to the requirements of a DNA synthesis process and a synthesis tool. In one example, the correspondence relationship between the row number and the DNA base sequence may include the correspondence relationship in table 2, and the correspondence relationship between the segment number and the DNA base sequence may include the correspondence relationship in table 3.

TABLE 2 encoding of "line number" in index tag

Line number	0	1	2	3	4	5	6	7	8	9
											Encoding	TA	TC	TG	AT	AC	AG	CG	CT	GT	GC

TABLE 3 encoding of "segment number" in index tag

Segment number	0	1	2	3	4	5	6	7	8	9
											Encoding	TA	TC	TG	AT	AC	AG	CG	CT	GT	GC

In step S18, adding a base sequence corresponding to an index mark to the DNA fragment, where the index mark includes a level of the sub-image corresponding to the DNA fragment, pixel information of the sub-image corresponding to the DNA fragment, a type of the sub-image corresponding to the DNA fragment, and a line number and a segment number of the DNA fragment.

In the embodiment of the present disclosure, the level of the sub-image may include that in the above embodiment, the original image is wavelet-transformed by using a wavelet transform function, which is described with reference to fig. 3, where 1, 2, and 3 represent the level number of the sub-image. The pixel information may include YUV information of the sub-image pixels in the above embodiments. The types of the sub-images may include a series of sub-images with different frequencies or different components (i.e., horizontal component, vertical component, or diagonal component) obtained by wavelet transforming the original image in the above example, such as HL1, LH1, HH1, and HL2, LH2, HH 2.

In the embodiment of the present disclosure, the index marker is added to the DNA fragment, a DNA base sequence corresponding to the index marker needs to be obtained first, and the corresponding relationship between the index marker and the DNA base sequence may be established in advance. The correspondence between the neutron images of the index markers and the DNA base sequences may include a one-to-one correspondence as shown in table 4. Where Y0 denotes a low-frequency sub-image of brightness, Y50 denotes a five-level high-frequency horizontal sub-image of brightness, Y51 denotes a five-level high-frequency vertical sub-image of brightness, Y52 denotes a five-level high-frequency diagonal sub-image of brightness, Y40 denotes a four-level high-frequency horizontal sub-image of brightness, Y41 denotes a four-level high-frequency vertical sub-image of brightness, and Y42 denotes a four-level high-frequency diagonal sub-image of brightness. Y30 denotes a three-level high-frequency horizontal sub-image of brightness, Y31 denotes a three-level high-frequency vertical sub-image of brightness, and Y32 denotes a three-level high-frequency diagonal sub-image of brightness. Y20 denotes a secondary high-frequency horizontal sub-image of brightness, Y21 denotes a secondary high-frequency vertical sub-image of brightness, and Y22 denotes a secondary high-frequency diagonal sub-image of brightness. U0 denotes a low frequency sub-image of a color, U50 denotes a five-level high frequency horizontal sub-image of a color, U51 denotes a five-level high frequency vertical sub-image of a color, U52 denotes a five-level high frequency diagonal sub-image of a color, a four-level high frequency horizontal sub-image of a U40 color, U41 denotes a four-level high frequency vertical sub-image of a color, and U42 denotes a four-level high frequency diagonal sub-image of a color. V0 denotes a low-frequency sub-image of saturation, V50 denotes a five-level high-frequency horizontal sub-image of saturation, V51 denotes a five-level high-frequency vertical sub-image of saturation, V52 denotes a five-level high-frequency diagonal sub-image of saturation, V40 denotes a four-level high-frequency horizontal sub-image of saturation, V41 is a four-level high-frequency vertical sub-image of saturation, and V42 denotes a four-level high-frequency diagonal sub-image of saturation. The base sequences corresponding to the row number and the segment number in the index markers can be obtained from tables 2 and 3.

TABLE 4 coding of "subimage information" in index markers

Y

Y0

Y51

Y52

Y40

Y41

Y42

Coding of Y

AAT

ACG

AGA

AGT

ACA

ACT

ACC

Y

Y30

Y31

Y32

Y20

Y21

Y22

Coding of Y

TGA

ATC

ATG

AAC

AAG

ATA

U

U0

U50

U51

U52

U40

U41

U42

Coding of U

AGC

TAC

TAG

TTA

AGG

TGT

TAT

V

V0

V50

V51

V52

V40

V41

V42

Coding of V

TGC

TCT

TCC

TCG

TTC

TTG

TCA

In the embodiment of the present disclosure, the index mark is not limited to include the level of the sub-image corresponding to the DNA segment, the pixel information of the sub-image corresponding to the DNA segment, the type of the sub-image corresponding to the DNA segment, and the line number and the segment number of the DNA segment, and may further include maximum absolute value information of the wavelet transform coefficient corresponding to the sub-image, and in one example, the maximum absolute value information may be added to the target wavelet transform coefficient corresponding to the sub-image according to the following format: "grade number + predetermined base label + maximum absolute value + grade number + predetermined base label". Wherein the grade number represents the grade number of the subimage, and the preset base label can be as "GTGTGTTATA", and when coding, the DNA base sequence corresponding to the grade number and the maximum absolute value needs to be added to the coding DNA sequence corresponding to the subimage. For example, the maximum absolute value of the five-level low-frequency horizontal sub-image is 7654, the maximum absolute value 7654 can be encoded according to the DNA base sequence corresponding to the number in table 1, which is denoted as "S + Z + P + B", the DNA base sequence corresponding to the level "five" is "AAT", the preset base mark is "GTGTGTTATA", and then the maximum absolute value 7654 of the five-level low-frequency horizontal sub-image is denoted as: "AATGTGTGTGTTATASZPBAATGTGTGTTTATA". The level number and the preset base label appear at the front end and the rear end of the maximum absolute value, which is beneficial to the check during decoding, for example, when the level number and the preset base label are read firstly, and then the base sequence corresponding to the maximum absolute value is read, the level number and the preset base label are read again, and when the level number and the preset base label which are read for the first time are different, the coding DNA sequence is indicated to have an error.

In the embodiment of the disclosure, the index mark is added to the DNA segment, and the index mark includes the level of the sub-image corresponding to the DNA segment, the pixel information of the sub-image corresponding to the DNA segment, the type of the sub-image corresponding to the DNA segment, and the line number and the segment number of the DNA segment, so that the content object included in the DNA segment can be accurately identified during the later decoding, and the DNA segment can be spliced.

In the embodiment of the present disclosure, base sequences corresponding to the index markers are added to the front and rear ends of the DNA fragment. The method has the advantages that when the index mark at the front end of the DNA segment is read for the first time and then the index mark at the rear end of the DNA segment is read again during image decoding, if the index marks read twice are not consistent, an error occurs in the DNA segment synthesis process. This piece of DNA is discarded and the correct synthesis of said piece of DNA is sought, typically the piece of DNA is synthesized and made up multiple times for the same piece. In one possible implementation manner, the base sequences corresponding to the index markers are added to the front and rear ends of the DNA fragment, respectively, as shown in Table 5.

TABLE 5 nucleic acid fragment Structure

In the examples of the present disclosure, the synthetic bases Z, P, S and B used include DNA molecule sequences with eight letters created by american scientist stevena. Complementary unnatural bases can recognize and bind to each other, form a double helix structure, and remain stable.

In the disclosed embodiment, the base sequence of the DNA may be natural genetic material: adenine A, guanine G, cytosine C and thymine T, and also can adopt artificially synthesized bases Z, P, S and B, the pairing mode of the bases Z and S is that the base Z is matched with the base P, and the base S is matched with the base B, which are all connected through three hydrogen bonds, and the corresponding relation is established through the permutation and combination of 8 bases and wavelet coefficients, thereby greatly reducing the digit of DNA base sequences and effectively reducing the data storage amount.

The following describes advantageous effects of the image storage method according to the present disclosure with reference to fig. 8. The wavelet transform coefficient of the U information of the five-level low-frequency horizontal sub-image obtained after the wavelet transform is performed on the original image in fig. 8 is shown in table 6, where table 6 only displays part of the data, and only the first 5 rows of the wavelet transform coefficient of the U information of the five-level low-frequency horizontal sub-image are taken here for space.

TABLE 6 partial data of U information wavelet transform coefficients for five-level low-frequency horizontal partial sub-images

And dividing each numerical value in the table 6 by the maximum absolute value of the U information wavelet transform coefficient, and reserving two decimal places to obtain a table 7. The decimal part in Table 7 is encoded into DNA sequence according to the correspondence between the DNA base sequence and the number in the above examples, and the first five elements of the DNA sequence are taken as examples as follows:

first row:

CZTATATCTATCTGPGTGZSTGACBTGZPTGAACTGAACTGACTTGAABTGAAPTGATPTGSZTGZTTGBSTG TCTGCATGZTGATTGACTGASTGCATGABTGSBTGACATGZZTGSATGPCTGTBTGTS

a second row:

CZTATATGTATCTGGCTGTZTGSBTGSGTGAASTGSPTGAATTGAAATGAAPTGAGPTGSZTGPPTGPTTGZ GTGGCTGCATGATTGAPTGABTGCTTGCPTGZPTGSPTGZTTGSATGBSTGBSTGTA

third row:

CZTATAATTATCTGGTTGBCTGSZTGSTTGAATTGPTTGBPTGPCTGZTTGAATTGPZTGGBTGTTTGGBTGC ZTGASTGACTGAPTGASTGCPTGCPTGZGTGSTTGZPTGPZTGPATGPPTGCZ

fourth row:

CZTATAACTATCTGCGTGGZTGPBTGSBTGSPTGZATGPTTGBGTGZSTGSPTGZATGPTTGBTTGBATGCTT GAGTGATTGAPTGABTGCBTGCBTGPBTGSATGSATGPPTGPGTGPPTGTP

the fifth element:

CZTATAAGTATCTGBSTGPPTGSATGSATGZTTGBGTGTBTGTTTGPPTGZPTGBPTGTGTGGZTGGATGABT GATTGASTGAPTGAZTGCZTGCBTGBSTGZTTGSPTGBPTGPGTGTBTGPG

TABLE 7 post fractional data after processing of U information wavelet transform coefficients for five-level low frequency horizontal partial sub-images

And (3) storing the number statistics of the DNA into the wavelet transformed coefficients: the number of encoded pieces of luminance information Y is as follows: synthesizing 1485 coding DNA sequences by the secondary subgraph; synthesizing 687 coding DNA sequences by the tertiary subimage; synthesizing 236 encoding DNA sequences by four levels of subimages; synthesizing 78 coding DNA sequences by the five-level subimage; the number of encoded pieces of chrominance information U is as follows: synthesizing 235 coding DNA sequences by four levels of subimages; synthesizing 77 coding DNA sequences by using the five-level subimage; the number of pieces of saturation information V encoded is as follows: synthesizing 230 coding DNA sequences by four levels of subimages; five levels of subimages synthesize 76 encoding DNA sequences. FIG. 11 shows 3104 total synthetic coding DNA sequences. The present disclosure has 10.3 times the coding efficiency of the fountain code method compared to the existing generally recognized better coding technique (fountain code method).

The image reading method according to the present disclosure will be described in detail below with reference to fig. 9. Fig. 9 is a flowchart of a method of an embodiment of an image reading method provided by the present disclosure. Although the present disclosure provides method steps as illustrated in the following examples or figures, more or fewer steps may be included in the method based on conventional or non-inventive efforts. In steps where no necessary causal relationship exists logically, the order of execution of the steps is not limited to that provided by the disclosed embodiments.

Specifically, as shown in fig. 9, an embodiment of an image reading method provided by the present disclosure includes:

step S21, extracting a DNA sequence corresponding to the sub-image according to the stored DNA sequence of the original image;

step S22, determining a wavelet transform coefficient corresponding to the pixel data of the sub-image according to the DNA sequence corresponding to the sub-image and the corresponding relation between the DNA base sequence and the wavelet transform coefficient;

step S23, performing inverse wavelet transform processing on the wavelet transform coefficient to obtain a decoded image of the original image.

In the embodiment of the present disclosure, in consideration of the influence of a DNA synthesis process, the coding DNA sequence of the original image is cut into a plurality of nucleic acid segment structures, in one example, the nucleic acid segment structures are shown in table 5, and the nucleic acid segment structures are obtained, and the content of the index mark and the content of the wavelet transform coefficient corresponding to the sub-image can be distinguished according to the preset number of base sequence bits of the index mark, for example, the first 20nt is a flanking primer sequence and 8-15nt is an index coding sequence in table 5.

In the embodiments of the present disclosure, according to the correspondence between the base sequence of the index mark and the number, in one example, the index mark includes: the level of the subimage corresponding to the DNA segment, the pixel information of the subimage corresponding to the DNA segment, the type of the subimage corresponding to the DNA segment, and the line number and the segment number of the DNA segment, according to the correspondence between the subimage information and the DNA base sequence of the index marker in the above embodiment, including, for example, table 4, the correspondence between the line number and the base sequence of the DNA segment, including, for example, table 2, the correspondence between the segment number and the base sequence of the DNA segment, including, for example, table 3, the meaning of the index marker is decoded, and the subimage information includes the level number of the subimage, the pixel information, and the type marker of the subimage. In one example, the decoding of the DNA fragments of the same level sub-image into wavelet transform coefficients according to the correspondence relationship between the DNA fragment sequences and numbers, which is the same as the correspondence relationship in the above embodiment, may include the correspondence relationship as in table 1.

In one example, for the decoded wavelet transform coefficient, the wavelet transform coefficient of the missing sub-image may be subjected to wavelet inverse transform by complementing 0 to obtain a decoded image.

Fig. 10 is a block diagram illustrating an image storage apparatus 800 according to an exemplary embodiment, and fig. 10 is a block diagram similarly applicable to an image reading apparatus. For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.

Referring to fig. 10, the apparatus 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.

The processing component 802 generally controls overall operation of the device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operations at the apparatus 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

Power components 806 provide power to the various components of device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the apparatus 800.

The multimedia component 808 includes a screen that provides an output interface between the device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the device 800. For example, the sensor assembly 814 may detect the open/closed status of the device 800, the relative positioning of components, such as a display and keypad of the device 800, the sensor assembly 814 may also detect a change in the position of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration/deceleration of the device 800, and a change in the temperature of the device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate communications between the apparatus 800 and other devices in a wired or wireless manner. The device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the device 800 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

Fig. 11 is a block diagram illustrating an image storage device 1900 according to an exemplary embodiment, and fig. 11 is a block diagram similarly applicable to an image reading device. For example, the apparatus 1900 may be provided as a server. Referring to FIG. 11, the device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by the processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the image storing method or the image reading method according to any of the embodiments described above.

The device 1900 may also include a power component 1926 configured to perform power management of the device 1900, a wired or wireless network interface 1950 configured to connect the device 1900 to a network, and an input/output (I/O) interface 1958. The device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.

In an exemplary embodiment, a non-transitory computer readable storage medium is also provided that includes instructions, such as the memory 1932 that includes instructions, which are executable by the processing component 1922 of the apparatus 1900 to perform the above-described method. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An image storage method, comprising:

performing wavelet transformation on the low-frequency sub-image subjected to wavelet transformation on the original image for multiple times to obtain wavelet transformation coefficients corresponding to the multi-level sub-image;

adjusting the wavelet transform coefficients of the sub-image so that the adjusted wavelet transform coefficients match the pixel information of the sub-image, comprising: the level of the sub-image selected by encoding the pixel brightness type wavelet transform coefficient is more when the pixel information is the pixel brightness than when the pixel information is the pixel chroma or the pixel saturation;

encoding the target wavelet transform coefficient into a DNA sequence according to a preset corresponding relation between the DNA base sequence and the wavelet transform coefficient, comprising: acquiring the sign and the value of the wavelet transform coefficient; respectively coding the signs and the numerical values of the wavelet transform coefficients into DNA sequences according to the corresponding relation between the DNA base sequences and the signs and the corresponding relation between the DNA base sequences and the numerical values; if N is more than or equal to 2 when N identical continuous numbers appear in the numerical values, the wavelet transform coefficient is coded into a DNA sequence according to the following format: "marker + DNA base sequence corresponding to numerical value N".

2. The method according to claim 1, wherein after encoding the target wavelet transform coefficients into a DNA sequence according to the preset correspondence between the DNA base sequences and the wavelet transform coefficients, the method further comprises:

cutting the DNA base sequence of the same line number according to a preset length value to obtain an X segment of DNA fragment, wherein X is more than or equal to 1;

3. The method of claim 2, wherein the adding of the base sequence corresponding to the index marker to the DNA fragment comprises:

4. The method according to any one of claims 1 to 3, wherein the DNA base sequence comprises at least one of natural base A, base G, base T and base C and synthetic base Z, base P, base S and base B.

5. The method according to claim 1, further comprising an image reading method comprising:

extracting a DNA sequence corresponding to the subimage according to the stored DNA sequence of the original image;

and performing inverse wavelet transform processing on the wavelet transform coefficient to obtain a read image of the original image.

6. An image storage apparatus, comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform the storage method of any one of claims 1 to 4.

7. An image reading apparatus, characterized by comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform the reading method of claim 5.

8. A non-transitory computer-readable storage medium, wherein instructions in the storage medium, when executed by a processor, enable the processor to perform the storage method of any one of claims 1 to 4.

9. A non-transitory computer-readable storage medium, wherein instructions in the storage medium, when executed by a processor, enable the processor to perform the reading method according to claim 5.