Abstract:
In an image data processing system, an insignificant space estimation unit predicts a significant/insignificant space in a high-frequency subband on the basis of a low-frequency subband signal in a wavelet space. A deletion unit deletes data in the insignificant space which is predicted by the insignificant space estimating unit. Here, the data is contained in the high-frequency subband. An error-estimation detection unit detects presence of significant data in the space predicted to be insignificant by the insignificant space estimation unit. An adding unit adds to output data a significance attribute indicating that significant data exists in the space detected by the error-estimation detection unit.

Description:
BACKGROUND OF THE INVENTION 
     The present invention relates to an image data processing method and an image data processing system which can be adopted or employed in image data compression processing and the like. 
     In the high-efficiency coding technique of the image for which the use of communication media and/or recording media is prerequisite, the technique based on discrete cosine transform (DCT) is extensively adopted. However, one of the intrinsic problems inherent to the compression procedure using the DCT can be seen in that when the compression ratio is increased, then block distortions, mosquito noise and the like will become visually perceived, imposing thus limitation on the realizable compression ratio. 
     Under the circumstances, the novel compression procedures have been developed and proposed in recent years in an attempt for enhancing the compression ratio. Among others, the data compression technique adopting a so-called wavelet transformation, one of the subband encoding techniques, attracts attention. Parenthetically, this technique will hereinafter be referred to as the wavelet. As the wavelet lacks the concept of “block”, there is no inter-block distortion generated in the DCT, so that the image quality is visually improved to an appreciable extent. 
     For having better understanding of the present invention, a conventional wavelet compression/expansion method known heretofore will be described in some detail. 
     FIG. 7 is a block diagram showing generally and schematically a system configuration of a conventional wavelet image compression system. In the figure, reference numeral  1001  denotes an original image. Reference numerals  1002 ,  1003  and  1004  denote subband decomposition units for layer- 0 , layer- 1  and layer- 2  provided at stages # 0 , # 1  and # 2 , respectively. Reference numeral  1005  denotes an insignificant-space-estimation deletion unit. 
     FIG. 11 is a block diagram which shows representatively a structure of the subband decomposition unit shown in FIG.  7 . In FIG. 11, reference numeral  1401  denotes a horizontal low-pass filter,  1402  denotes a horizontal high-pass filter,  1403   1  and  1403   2  denote horizontal down-samplers,  1404   1 , and  1404   2  denote vertical low-pass filters,  1405   1  and  1405   2  denote vertical high-pass filters, and reference numerals  1406   1 - 1406   4  denote vertical down-samplers. 
     For carrying out the wavelet transformation, the horizontal low-pass filter  1401  receives two-dimensional input data  1455  shown in FIG. 11 to perform the low-frequency filtering operation in the horizontal direction. Thereby, horizontal low-frequency data  1456  is generated. The horizontal high-pass filter  1402  receives the two-dimensional input data  1455  to perform the high-frequency filtering operation in the horizontal direction. Thereby, horizontal high-frequency data  1457  is generated. These data  1456  and  1457  then undergo the horizontal down-sampling operation by the horizontal down-samplers  1403   1  and  1403   2 , respectively. Thereby, horizontal DC separate data  1458  and horizontal H separate data  1459  are generated. 
     The horizontal DC separate data  1458  then undergoes the filtering operation in the vertical direction by the vertical low-pass filter  1404   1 , and the vertical high-pass filter  1405   1  to generate horizontal DC vertical low-frequency data  1460  and horizontal DC vertical high-frequency data  1461 , respectively. Similarly, the horizontal H separate data  1459  undergoes the filtering operation in the vertical direction by the vertical low-pass filter  1404   2  and the vertical high-pass filter  1405   2  to generate horizontal H vertical low-frequency data  1462  and horizontal H vertical high-frequency data  1463 , respectively. These data  1460 - 1463  then undergo the vertical down-sampling operation by the vertical down-samplers  1406   1 - 1406   4  to generate DC separate data  1451 , LH separate data  1452 , HL separate data  1453  and HH separate data  1454 , respectively. In this way, the wavelet transformation can be realized. The subband decomposition processing at the succeeding stage is performed substantially in the same manner. 
     FIG. 9 is a block diagram showing generally and schematically a system configuration of a conventional wavelet image expansion system. In FIG. 9, reference numeral  1101  denotes an insignificant-space-estimation development unit,  1102  denotes a layer- 0  subband synthesis unit,  1103  denotes a layer- 1  subband synthesis unit, and  1104  denotes a layer- 2  subband synthesis unit. Reference numeral  1105  denotes an expanded image. 
     FIG. 8 is a block diagram showing generally and schematically an arrangement of the conventional insignificant-space-estimation deletion unit  1005  shown in FIG.  7 . In FIG. 8, reference numeral  1201  denotes a layer- 1  HL insignificant space estimation module for estimating an HL insignificant space of the layer- 1  on the basis of the layer- 2  HL space. Reference numeral  1202  denotes a layer- 1  LH insignificant space estimation module for estimating an LH insignificant space of the layer- 1  on the basis of the layer- 2  LH space. Reference numeral  1203  denotes a layer- 1  HH insignificant space estimation module for estimating an HH insignificant space of the layer- 1  on the basis of the layer- 2  HH space. Reference numerals  1204 ,  1205  and  1206  denote a layer- 1  HL insignificant space deletion module, a layer- 1  LH insignificant space deletion module, a layer- 1  HH insignificant space deletion module, respectively, for deleting the relevant insignificant spaces in the layer- 1 . Reference numerals  1207 ,  1208  and  1209  denote layer- 0  HL, LH and HH insignificant space estimation modules for estimating relevant insignificant spaces in the layer- 0  from the HL, LH and HH insignificant spaces of the layer- 1 , respectively. Reference numerals  1210 ,  1211  and  1212  denote HL, LH and HH insignificant space deletion modules for deleting the HL, LH and HH insignificant spaces of the layer- 0 , respectively. 
     FIG. 10 is a block diagram showing a structure of the conventional insignificant-space-estimation development unit  1101  shown in FIG.  9 . In FIG. 10, reference numeral  1301  denotes a layer- 1  HL development module,  1302  denotes a layer- 1  LH development module,  1303  denotes a layer- 1  HH development module,  1304  denotes a layer- 0  HL development module,  1305  denotes a layer- 0  LH development module, and  1306  denotes a layer- 0  HH development module. 
     FIG. 12 is a block diagram showing a structure of the subband synthesis unit (see FIG.  9 ). In FIG. 12, reference numerals  1501   1 - 1501   4  denote vertical up-samplers,  1502   1 , and  1502   2  denote vertical low-pass filters,  1503   1 , and  1503   2  denote vertical high-pass filters,  1504   1  and  1504   2  denote horizontal up-samplers,  1505  denotes a horizontal low-pass filter, and  1506  denotes a horizontal high-pass filter. 
     Next, description will be directed to the operation of the conventional wavelet compression/expansion system. When the original image  1001  is supplied, the layer- 0  subband decomposition unit  1002  shown in FIG. 7 receives the original image data  1061  to perform the first wavelet transformation. Thereby, wavelet data (i.e., layer- 0  DC data  1062 , layer- 0  HL data  1063 , layer- 0  LH data  1064  and layer- 0  HH data  1065 ) are generated. These wavelet data will hereinafter be referred to as layer- 0  wavelet data. 
     The layer- 1  subband decomposition unit  1003  receives the layer- 0  wavelet DC data  1062  to perform the second wavelet transformation. Thereby, wavelet data (i.e., layer- 1  DC data  1066 , layer- 1  HL data  1067 , layer- 1  LH data  1068  and layer- 1  HH data  1069 ) are generated. These wavelet data will hereinafter be referred to as layer- 1  wavelet data. 
     Then, the layer- 2  subband decomposition unit  1004  receives the layer- 1  DC wavelet data  1066  to perform the third wavelet transformation. Thereby, wavelet data (i.e., layer- 2  DC data  1051 , layer- 2  HL data  1052 , layer- 2  LH data  1053 , and layer- 2  HH data  1054 ) are generated. These wavelet data will hereinafter be referred to as layer- 2  wavelet data. 
     In order that the data compression is performed on the basis of the correlation in the frequency direction among the wavelet data generated in the manners mentioned above, the insignificant-space-estimation deletion unit  1005  receives the wavelet data  1052 - 1054 ,  1067 - 1069 , and  1063 - 1065  which contain no DC component. Then, the insignificant-space-estimation deletion unit  1005  performs the data compression by deleting the insignificant spaces. 
     FIG. 13 is a view for illustrating the wavelet space. In the figure, reference numerals  1601 ,  1602  and  1603  denote HH, LH and HL wavelet spaces of the layer- 0 , respectively. Reference numerals  1604 ,  1605  and  1606  denote HH, LH and HL wavelet spaces of the layer- 1 , respectively. Reference numerals  1607 ,  1608  and  1609  denote HH, LH and HL wavelet spaces of the layer- 2 , respectively. Reference numeral  1610  denotes a layer- 2  DC wavelet space. 
     It is to be mentioned that the wavelet data exhibits the correlation between the adjacent layers. For example, when a value held by a given area  1652  in the space  1606  that is the wavelet data of the layer- 1  is small, then the value held by an analogous area  1651  in the space  1603  that is the wavelet data of layer- 0  having the same component can be regarded to be small with a high probability. Further, when the value of the given area  1652  is sufficiently small, the analogous area  1651  in the space  1603  may be defined as having a minimum value. In that case, the data of the analogous area  1651  is unnecessary for the decoding so far as the data of the given area  1652  is available. Accordingly, when the value of the given area  1652  is detected to be smaller than a given threshold value in the coding processing, the analogous area  1651  in the adjacent layer can be decided to be an insignificant space to be deleted from the space  1603 . As a result, it can contribute to the improvement of the data compression efficiency. Upon the decoding, the value of the given area  1652  is checked. When it is found that the value of the given area  1652  is not greater than the threshold value referenced at the time of coding, the wavelet space can be reconstituted by embedding the minimum value in the space  1603 . 
     Now, description will be made in concrete of the processing for deleting the insignificant space as executed by the insignificant-space-estimation deletion unit  1005 . In FIG. 8, the layer- 1  HL insignificant space estimation module  1201  receives the layer- 2  HL wavelet data  1052  to perform the threshold value decision. Thereby, the minimum-value-area estimation of the layer- 1  HL data  1067  that is the data of the layer lower by one rank than the data  1052  is performed to generate the layer- 1  HL insignificant space estimation data  1251 . Similarly, the other insignificant space estimation modules  1202  and  1203  receive the relevant wavelet data of the layer- 2  (i.e., the layer- 2  LH data  1053  and the layer- 2  HH data  1054 ) to perform the minimum-value-area estimation in the data of the one-rank lower layer (i.e., layer- 1 ). Thereby, the layer- 1  LH insignificant space estimation data  1252  and the layer- 1  HH insignificant space estimation data  1253  are generated. 
     The layer- 1  HL insignificant space deletion module  1204  receives the layer- 1  HL insignificant space estimation data  1251  and the layer- 1  HL data  1067  to delete the data in the insignificance-estimated area. Thereby, the layer- 1  HL compressed data  1055  is generated. In a similar manner, the layer- 1  LH insignificant space deletion module  1205  generates the layer- 1  LH compressed data  1056  on the basis of the layer- 1  LH insignificant space estimation data  1252  and the layer- 1  LH data  1068 . Further, the layer- 1  HH insignificant space deletion module  1206  generates the layer- 1  HH compressed data  1057  on the basis of the layer- 1  HH insignificant space estimation data  1253  and the layer- 1  HH data  1069 . 
     Similarly, the layer- 0  insignificant space estimation modules  1207 ,  1208  and  1209  receive the layer- 1  compressed data  1055 ,  1056  and  1057  to perform the minimum-value-area estimation of the data in the one-rank lower layer (i.e., the layer- 0 ), respectively. Thereby, the layer- 0  insignificant space estimation data  1254 ,  1255  and  1256  are generated. Then, the layer- 0  compressed data are generated on the basis of the layer- 0  insignificant space estimation data  1254 ,  1255  and  1256 . 
     Next, description will turn to the operation of the conventional decoder implemented in the form of the wavelet image expansion unit. In FIG. 9, the layer- 0  subband synthesis unit  1102  receives the compressed wavelet data of the layer- 2  (i.e., the layer- 2  DC data  1051 , the layer- 2  HL data  1052 , the layer- 2  LH data  1053  and the layer- 2  HH data  1054 ) to perform the reverse wavelet transformation. Thereby, the layer- 1  DC expanded data  1158  is generated. 
     In this conjunction, the reverse wavelet transformation can be realized by means of the vertical p-sampler  1501   1 , shown in FIG. 12 that receives the DC input data  1552  to perform the up-sampling operation in the vertical direction. Thereby, the DC up-sampled data  1556  is generated. Likewise, the vertical up-samplers  1501   2 - 1501   4  receive the HL input data  1553 , the LH input data  1554  and the HH input data  1555  to generate the up-sampled data  1557 ,  1558  and  1559 , respectively. 
     Subsequently, the vertical low-pass filter  1502   1  and the vertical high-pass filter  1503   1  receive the DC up-sampled data  1556  and the HL up-sampled data  1557 , respectively, to perform the filtering reverse mapping transformation in the vertical direction. Thereby, the horizontal DC synthesized data  1560  is generated. Likewise, the vertical low-pass filter  1502   2  and the vertical high-pass filter  1503   2  receive the LH up-sampled data  1558  and the HH up-sampled data  1559 , respectively, to generate the horizontal H synthesized data  1561 . 
     The horizontal up-sampler  1504   1  receives the horizontal DC synthesized data  1560  to perform the up-sampling operation in the horizontal direction. Thereby, the horizontal DC up-sampled data  1562  is generated. Similarly, the horizontal up-sampler  1504   2  receives the horizontal H synthesized data  1561  to generate the horizontal H up-sampled data  1563 . The horizontal low-pass filter  1505  and the horizontal high-pass filter  1506  receive the horizontal DC up-sampled data  1562  and the horizontal H up-sampled data  1563 , respectively, to perform the filtering reverse mapping transformation in the horizontal direction. Thereby, the synthesized data  1551  is generated. 
     In FIG. 9, the insignificant-space-estimation development unit  1101  receives the data  1052 - 1060  of the individual layers to decode the data compressed by deleting the insignificant spaces. Thereby, the expanded data  1152 - 1157  of the individual layers are generated. 
     Now, concrete description will be made of the decoding of the data compressed by deleting the insignificant spaces. FIG. 10 is a block diagram showing concretely the structure of the insignificant-space-estimation development unit  1101 . In FIG. 10, the insignificant space estimation module  1201  receives the layer- 2  HL data  1052  to estimate the minimum value area in the data of the one-rank lower layer (i.e., the layer- 1  HL compressed data  1055 ). Thereby, the HL insignificant space development/estimation data  1351  is generated. Similarly, the insignificant space estimation modules  1202  and  1203  receive the component data of the layer- 2  (i.e., the layer- 2  LH data  1053  and the layer- 2  HH data  1054 ) to estimate the minimum value areas in the data of the respective one-rank lower layer. Thereby, the layer- 1  LH insignificant space development/estimation data  1352  and the layer- 1  HH insignificant space development/estimation data  1353  are generarted. 
     The layer- 1  HL development module  1301  receives the layer- 1  HL insignificant space development/estimation data  1351  and the layer- 1  HL compressed data  1055  to embed the minimum value in the insignificance-estimated area. Thereby, the HL expanded data  1152  is generated. Similarly, the layer- 1  LH development module  1302  generates the LH expanded data  1153  by embedding the minimum value in the insignificance-estimated area on the basis of the layer- 1  LH compressed data  1056  and the layer- 1  LH insignificant space development/estimation data  1352 . The layer- 1  HH development module  1303  generates the HH expanded data  1154  by embedding the minimum value in the insignificance-estimated area on the basis of the layer- 1  HH compressed data  1057  and the layer- 1  HH insignificant space development/estimation data  1353 . 
     Then, the layer- 0  HL insignificant space estimation module  1207  receives the layer- 1  HL expanded data  1152  to perform the threshold value decision for estimating the minimum value area in the data of the one-rank lower layer (i.e., the layer- 0  HL compressed data  1058 ). Thereby, the layer- 0  HL insignificant space development/estimation data  1354  is generated. Similarly, the layer- 0  LH insignificant space estimation module  1208  receives the component data of the layer- 1  (i.e., the layer- 1  LH expanded data  1153 ) to estimate the minimum value area in the data of the one-rank lower layer. Thereby, the layer- 0  LH insignificant space development/estimation data  1355  is generated. The layer- 0  HH insignificant space estimation module  1209  receives the component data of the layer- 1  (i.e., the layer- 1  HH expanded data  1154 ) to estimate the minimum value area in the data of the one-rank lower layer. Thereby, the layer- 0  HH insignificant space development/estimation data  1356  is generated. 
     Finally, the layer- 0  HL development module  1304  receives the layer- 0  HL insignificant space development/estimation data  1354  and the layer- 0  HL compressed data  1058  to embed the minimum value in the insignificance-estimated area. Thereby, the layer- 0  HL expanded data  1155  is generated. Similarly, the layer- 0  LH development module  1305  generates the layer- 0  LH expanded data  1156  by embedding the minimum value to the insignificance-estimated area on the basis of the layer- 0  LH compressed data  1059  and the layer- 0  LH insignificant space development/estimation data  1355 . The layer- 0  HH development module  1306  generates the layer- 0  HH expanded data  1157  by embedding the minimum value to the insignificance-estimated area on the basis of the layer- 0  HH compressed data  1060  and the layer- 0  HH insignificant space development/estimation data  1356 . In this way, the decoding of the wavelet data is carried out. 
     In FIG. 9, reference numeral  1158  designates layer- 1  DC expanded data, and  1159  designates layer- 0  DC expanded data. Reference numeral  1151  designates the expanded image data. The layer- 1  subband synthesis unit  1103  receives the wavelet data  1158 ,  1152 ,  1153  and  1154  of the layer- 1  to generate the layer- 0  DC expanded data  1159 . Further, the layer- 2  subband synthesis unit  1104  receives the wavelet data  1159 ,  1155 ,  1156  and  1157  of the layer- 0  to generate the expanded image data  1151 . Through the procedure described above, the image data can be expanded. 
     However, the conventional image data processing system suffers shortcomings that the accuracy in predicting or estimating the insignificant area is relatively low, incurring degradation in the image compression efficiency. More specifically, for a signal having only high frequency components, there may arise such situation that the high-frequency components are estimated as the insignificant spaces because of unavailability of the correlation between the low-frequency components and the high-frequency components. Thus, there are some cases where the degradation with regard to the resolution of the image is occurred. 
     SUMMARY OF THE INVENTION 
     It is an object of the present invention to provide an image data processing method and an image data processing system which can ensure the enhanced accuracy for the estimation of the insignificant space as well as the improvement for the image data compression efficiency. 
     In order to achieve the object, the present invention allows the insignificant space estimation of the high-frequency components with high accuracy and reliability by deleting an insignificant space from data with high accuracy in the following manner. Upon the prediction of a space in which significant data of high-frequency data after the subband division is exists, in the case that any significant data exists in the space estimated as an insignificant space, a significance attribute indicating the presence of insignificant data in the insignificance-decided space corresponding to the space in which it exists. Then, the insignificant space to be compressed is re-estimated on the basis of a threshold value of the insignificance-decided space added the significance attribute and the significance attribute. 
     The first aspect of the present invention is a coding or encoding apparatus for an image data processing system, which comprises: means for performing wavelet transformation; means for estimating and deleting an insignificant space to be subjected to code-deletion on the basis of a threshold decision for the insignificant space and significance attribute indicating presence of significant data; means for detecting the presence of the significant data in the space estimated as the insignificant space by the estimated means; and means for adding the significance attribute to the insignificance-decided space corresponding to the space in which the significant data exists. According to the first aspect, the accuracy of the prediction on the basis of the frequency correlation upon the coding can be enhanced. Thereby, the image quality degradation due to the compression can be prevented without increasing the amount of codes upon the coding. 
     The second aspect of the present invention is a decoding apparatus for an image data processing system, which comprises: means for estimating an insignificant space to be subjected to code-deletion on the basis of a threshold comparison decision of an insignificance-decided space and a significance attribute indicating presence of significant data; means for embedding an insignificant data in the space decided to be insignificant by the estimating means and for developing data generated by the coding method mentioned previously in the areas other than the insignificant space; and means for performing a reverse wavelet transformation. According to the second aspect, the accuracy of the prediction on the basis of the frequency correlation upon the decoding can be enhanced. Thereby, the image quality degradation of the expanded image can be prevented without increasing the amount of codes upon the coding. 
     The above and other objects, features and attendant advantages of the present invention will more easily be understood by reading the following description of the preferred embodiments thereof taken, only by way of example, in conjunction with the accompanying drawings. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     In the course of the description which follows, reference is made to the drawings, in which: 
     FIG. 1 is a block diagram showing generally and schematically a system configuration of a wavelet image compression system according to an embodiment of the present invention; 
     FIG. 2 is a block diagram showing schematically a structure of an insignificant-space-estimation deletion unit according to an embodiment of the present invention; 
     FIG. 3 is a view for illustrating detection of significant data in an insignificance-estimated space and addition of significance attribute according to an embodiment of the present invention; 
     FIG. 4 is a block diagram showing schematically a structure of a wavelet image expansion unit according to an embodiment of the present invention; 
     FIG. 5 is a block diagram showing schematically a structure of an insignificant-space-estimation development unit according to an embodiment of the present invention; 
     FIG. 6 is a view for illustrating operation of a significance attribute addition module according to an embodiment of the present invention; 
     FIG. 7 is a block diagram showing generally and schematically a system configuration of a conventional wavelet image compression system; 
     FIG. 8 is a block diagram showing an arrangement of the conventional insignificant-space-estimation deletion unit; 
     FIG. 9 is a block diagram showing schematically a structure of a conventional wavelet image expansion system; 
     FIG. 10 is a block diagram showing schematically a structure of the conventional insignificant-space-estimation development unit; 
     FIG. 11 is a block diagram showing representatively a structure of the subband decomposition unit shown in FIG. 7; 
     FIG. 12 is a block diagram showing schematically a structure of a conventional subband synthesis unit; and 
     FIG. 13 is a view for illustrating wavelet space. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Now, an image data processing method and an image data processing system for carrying out the same according to the present invention will be described in conjunction with preferred embodiments thereof by reference to the drawings. Incidentally, components or parts same as or equivalent to those mentioned hereinbefore in conjunction with the description of the conventional techniques made by reference to FIGS. 7 to  12  are designated by like reference characters and repeated description in detail thereof is omitted. 
     FIG. 1 is a block diagram showing a system configuration of a wavelet image compression system according to an embodiment of the present invention. In FIG. 1, reference numeral  1001  designates an original image. Reference numeral  1002  denotes a subband decomposition unit for performing a subband decomposition at a first stage (layer- 0 ). Hereinafter, this subband decomposition unit will be referred to as the layer- 0  subband decomposition unit. Reference numeral  1003  denotes a subband decomposition unit for performing a subband decomposition at a succeeding stage (layer- 1 ). Hereinafter, this subband decomposition unit will be referred to as the layer- 1  subband decomposition unit. Reference numeral  1004  denotes a subband decomposition unit for performing a subband decomposition at the final stage (layer- 2 ). Hereinafter, this subband decomposition unit will be referred to as the layer- 2  subband decomposition unit. Reference numeral  1061  designates original image data. The original image data  1061  is first supplied to the layer- 0  subband decomposition unit  1002  to be separated into subbands. 
     Reference numerals  1062 - 1065  designate subband data outputted from the layer- 0  subband decomposition unit  1002 . More specifically, reference numeral  1062  designates layer- 0  DC data,  1063  designates layer- 0  HL data,  1064  designates layer- 0  LH data, and  1065  designates layer- 0  HH data. The layer- 0  DC data  1062  is sent to the succeeding layer- 1  subband decomposition unit  1003 . 
     Reference numeral  101  denotes a layer- 0  HL error-estimation detection module,  102  denotes a layer- 0  LH error-estimation detection module, and  103  denotes a layer- 0  HH error-estimation detection module. These error-estimation detection modules are so designed as to detect a portion or area estimated erroneously as an insignificant space, and to output data indicating the presence of significant data. This data will hereinafter be referred to as the significance attribute data. Reference numeral  160  designates layer- 0  HL significance attribute data outputted from the layer- 0  HL error-estimation detection module  101 . Reference numeral  161  designates layer- 0  LH significance attribute data outputted from the layer- 0  LH error-estimation detection module  102 . Reference numeral  162  designates layer- 0  HH significance attribute data outputted from the layer- 0  HH error-estimation detection module  103 . 
     Reference numerals  1066 - 1069  designate data outputted from the layer- 1  subband decomposition unit  1003 . More specifically, reference numeral  1066  designates layer- 1  DC data,  1067  designates layer- 1  HL data,  1068  designates layer- 1  LH data, and  1069  designates layer- 1  HH data. The layer- 1  DC data  1066  is sent to the succeeding layer- 2  subband decomposition unit  1004 . 
     Reference numeral  1051  designates DC data outputted from the layer- 2  subband decomposition unit  1004 . This data will be referred to as the layer- 2  DC data. Reference numerals  1052 ,  1053  and  1054  designate layer- 2  HL data, layer- 2  LH data and layer- 2  HH data outputted from the layer- 2  subband decomposition unit  1004 , respectively. Reference numeral  151  designates layer- 2  HL compressed data,  152  designates layer- 2  LH compressed data, and  153  designates layer- 2  HH compressed data. 
     Reference numeral  104  denotes a layer- 2  HL significance attribute addition module which is so designed as to add to the layer- 2  HL data  1052  a significance attribute indicating that significant data exists in the portion decided by the layer- 0  HL error-estimation detection module  101  as having been erroneously estimated. The layer- 2  HL data  1052  with the significance attribute is outputted as layer- 2  HL compressed data  151  from the layer- 2  HL significance attribute addition module  104 . Similarly, reference numeral  105  denotes a layer- 2  LH significance attribute addition module which is so designed as to add to the layer- 2  LH data  1053  a significance attribute indicating that significant data exists in the portion decided by the layer- 0  LH error-estimation detection module  102  as having been erroneously estimated. The layer- 2  LH data  1053  with the significance attribute is outputted as layer- 2  LH compressed data  152  from the layer- 2  LH significance attribute addition module  105 . Reference numeral  106  denotes a layer- 2  HH significance attribute addition module which is designed so as to add to the layer- 2  HH data  1054  a significance attribute indicating that significant data exists in the portion decided by the layer- 0  HH error-estimation detection module  103  as having been erroneously estimated. The layer- 2  HH data  1054  with the significance attribute is outputted as layer- 2  HH compressed data  153  from the layer- 2  HH significance attribute addition module  106 . 
     Reference numeral  107  denotes an insignificant-space-estimation deletion unit which estimates an insignificant space on the basis of the attribute-affixed data and then delete the data in the insignificant space. The insignificant-space-estimation deletion unit  107  outputs an insignificance decision signal  163 . Reference numeral  154  designates layer- 1  HL compressed data,  155  designates layer- 1  LH compressed data, and  156  designates layer- 1  HH compressed data. Reference numeral  157  designates layer- 0  HL compressed data,  158  designates layer- 0  LH compressed data, and  159  designates layer- 0  HH compressed data. These compressed data are outputted from the insignificant-space-estimation deletion unit  107 . 
     FIG. 2 is a block diagram showing schematically a structure of the insignificant-space-estimation deletion unit  107  according to the embodiment of the present invention. In FIG. 2, reference numeral  301  denotes a layer- 1  HL insignificant space estimation module for estimating the layer- 1  HL insignificant space on the basis of the layer- 2  HL attribute-affixed data. Reference numeral  302  denotes a layer- 1  LH insignificant space estimation module for estimating the layer- 1  LH insignificant space on the basis of the layer- 2  LH attribute-affixed data. Reference numeral  303  denotes a layer- 1  HH insignificant space estimation module for estimating the layer- 1  HH insignificant space on the basis of the layer- 2  HH attribute-affixed space. Reference numeral  351  designates layer- 1  HL insignificant space estimation data outputted from the insignificant space estimation module  301 . Reference numeral  352  designates layer- 1  LH insignificant space estimation data outputted from the insignificant space estimation module  302 . Reference numeral  353  designates layer- 1  HH insignificant space estimation data outputted from the insignificant space estimation module  303 . 
     Reference numeral  304  denotes an estimation-result logical-ORing module for logically ORing the insignificant space estimation data  351 ,  352  and  353  of the subbands HL, LH and HH of the layer- 1 . Thus, for the area in any one of the subbands HL, LH and HH which is estimated as being insignificant, the estimation-result logical-ORing module  304  outputs an insignificance decision signal  163  indicating that the above-mentioned area is the insignificant space. 
     Reference numeral  1204  denotes a layer- 1  HL deletion module for deleting data in the area estimated to be the insignificant space from the layer- 1  HL data  1067 . The layer- 1  HL deletion module  1204  receives the layer- 1  HL insignificant space estimation data  351  and the layer- 1  HL data  1067 , and then deletes the data of the insignificance-estimated area indicated by the layer- 1  HL insignificant space estimation data  351  from the layer- 1  HL data  1067 . Thereby, layer- 1  HL compressed data  154  is outputted from the layer- 1  HL deletion module  1204 . Reference numeral  1205  designates a layer- 1  LH deletion module for deleting data in the area estimated as the insignificant space from the layer- 1  LH data  1068 . The layer- 1  LH deletion module  1205  receives the layer- 1  LH insignificant space estimation data  352  and the layer- 1  LH data  1068 , and then deletes the data of the insignificance-estimated area indicated by the layer- 1  LH insignificant space estimation data  352 . Thereby, layer- 1  LH compressed data  155  is outputted from the layer- 1  LH deletion module  1205 . Further, reference numeral  1206  designates a layer- 1  HH deletion module for deleting data in the area estimated to be the insignificant space from the layer- 1  HH data  1069 . The layer- 1  HH deletion module  1206  receives the layer- 1  HH insignificant space estimation data  353  and the layer- 1  HH data  1069 , and then deletes the data of the insignificance-estimated area indicated by the layer- 1  HH insignificant space prediction data  353 . Thereby, layer- 1  HH compressed data  156  is outputted from the layer- 1  HH deletion module  1206 . 
     Reference numeral  1207  denotes an insignificant space estimation module for estimating the insignificant space in the layer- 0  HL space on the basis of the layer- 1  HL space. Reference numeral  1208  denotes an insignificant space estimation module for estimating the insignificant space in the layer- 0  LH space on the basis of the layer- 1  LH space. Reference numeral  1209  denotes an insignificant space estimation module for estimating the insignificant space in the layer- 0  HH space on the basis of the layer- 1  HH space. Reference numeral  354  designates layer- 0  HL insignificant space estimation data,  355  designates layer- 0  LH insignificant space estimation data, and  356  designates layer- 0  HH insignificant space estimation data. 
     Reference numeral  1210  denotes a layer- 0  HL deletion module,  1211  denotes a layer- 0  LH deletion module, and  1212  denotes a layer- 0  HH deletion module. These modules  1210 ,  1211 ,  1212  delete data of the areas estimated as the insignificant spaces from the relevant data  1063 ,  1064  and  1065  of the layer- 0 , respectively, in the similar manner as the layer- 1  deletion modules  1204 ,  1205  and  1206  mentioned above. 
     According to the aspect of the present invention, in the case where some significant data exists in the space estimated as being the insignificant space, such processing is performed that the significance attribute indicating the presence of the significant data is added to the estimated insignificant space. More specifically, the layer- 0  HL error-estimation detection module  101  checks the layer- 0  HL data  1063  on the basis of the insignificance decision signal  163  to output the layer- 0  HL significance attribute data  160 . The layer- 0  LH error-estimation detection module  102  checks the layer- 0  LH data  1064  on the basis of the  20  insignificance decision signal  163  to output the layer- 0  LH significance attribute data  161 . Further, the layer- 0  HH error-estimation detection module  103  checks the layer- 0  HH data  1065  on the basis of the insignificance decision signal  163  to output layer- 0  HH significance attribute data  162 . When the significance attribute data  160 - 162  has been asserted (decided to be active), the data inputted to the relevant significance attribute addition modules  104 - 106  are affixed with the significance attribute. On the other hand, in the case where the individual significance attribute data mentioned above has been negated (decided to be inactive), no significance attribute is added. Consequently, the data inputted to the significance attribute addition modules  104 - 106  are outputted as the compressed data  151 - 153 . The detection of the significant data and the addition of the significance attribute are illustrated in FIG.  3 . 
     FIG. 4 is a block diagram showing schematically a  10  structure of a wavelet image expansion unit according to an embodiment of the present invention. Reference numeral  201  denotes an insignificant-space-estimation development unit,  202  denotes an HL significance attribute separating module,  203  denotes an LH significance attribute separating module,  204  denotes an HH significance attribute separating module,  1102  denotes a layer subband synthesis unit,  1103  denotes a layer- 1  subband synthesis unit,  1104  denotes a layer- 2  subband synthesis unit, and  1105  denotes an expanded image. 
     Reference numeral  252  designates layer- 2  HL significance-attribute-eliminated data,  253  designates layer- 2  LH significance-attribute-eliminated data, and  254  designates layer- 2  HH significance-attribute-eliminated data. Reference numeral  255  designates layer- 1  DC expanded data. 
     Reference numeral  256  designates layer- 1  HL expanded data,  257  designates layer- 1  LH expanded data,  258  designates layer- 1  HH expanded data, and  259  designates layer- 0  DC expanded data. Reference numeral  260  designates layer- 0  HL expanded data,  261  designates layer- 0  LH expanded data, and  262  designates layer- 0  HH expanded data. Reference numeral  251  designates expanded image data. 
     FIG. 5 is a block diagram showing a structure of the insignificant-space-estimation development unit according to the embodiment of the present invention. Reference numeral  451  designates layer- 1  HL insignificant space development/estimation data,  452  designates layer- 1  LH insignificant space development/estimation data, and  453  designates layer- 1  HH insignificant space development/estimation data. The insignificant space estimation modules  301 - 303  are implemented similarly to those shown in FIG.  2 . Reference numeral  454  designates layer- 0  HL insignificant space development/estimation data,  455  designates layer- 0  LH insignificant space development/estimation data, and  456  designates layer- 0  HH insignificant space development/estimation data. Reference numeral  1301  denotes a layer- 1  HL development module,  1302  denotes a layer- 1  LH development module,  1303  denotes a layer- 1  HH development module,  1304  denotes a layer- 0  HL development module,  1305  denotes a layer- 0  LH development module, and  1306  denotes a layer- 0  HH development module. 
     FIG. 6 is a view for illustrating operation of a significance attribute data adding module according to the embodiment of the present invention. Reference numeral  1609  designates a layer- 2  HL wavelet space, and  1603  designates a layer- 0  HL wavelet space. Reference numeral  501  designates layer- 0  HL fault significance data, and  502  designates layer- 2  estimation reference data. 
     Now, description will be directed to coding or encoding processing according to the instant embodiment. Upon the reception of the original image data  1061 , the layer- 0  subband decomposition unit  1002  performs the wavelet transformation to generate the wavelet data of layer- 0  (i.e., the-layer- 0  DC data  1062 , layer- 0  HL data  1063 , layer- 0  LH data  1064  and the layer- 0  HH data  1065 ). 
     The layer- 1  subband decomposition unit  1003  performs the wavelet transformation on the layer- 0  DC data  1062  as received, to thereby generate the wavelet data of layer- 1  (i.e., the layer- 1  DC data  1066 , layer- 1  HL data  1067 , layer- 1  LH data  1068  and the layer- 1  HH data  1069 ). 
     The layer- 2  subband decomposition unit  1004  performs the wavelet transformation on the layer- 1  DC data  1066  as received, to thereby generate the wavelet data of layer- 2  (i.e., the layer- 2  DC data  1051 , layer- 2  HL data  1052 , layer- 2  LH data  1053  and the layer- 2  HH data  1054 ). At this time point, all of the layer- 0  HL significance attribute data  160 , the layer- 0  LH significance attribute data  161  and the layer- 0  HH significance attribute data  162  are negated (i.e., decided to be inactive). 
     The layer- 2  HL data  1052  and the layer- 0  HL significance attribute data  160  are then received by the layer- 2  HL significant attribute addition module  104 . In that case, if the layer- 0  HL significance attribute data  160  has been asserted (decided to be active), then the layer- 2  HL significant attribute addition module  104  will generate the layer- 2  HL compressed data  151  by adding the significance attribute. However, at this time point, the layer-O HL significance attribute data  160  is negated (decided to be inactive). Accordingly, no significance attribute is added. Thus, the layer- 2  HL significant attribute addition module  104  generates a copy of the layer- 2  HL data  1052  as the layer- 2  HL compressed data  151 . 
     Likewise, upon the reception of the layer- 2  LH data  1053  and the layer-O LH significance attribute data  161 , the layer- 2  LH significance attribute addition module  105  generates a copy of the layer- 2  LH data  1053  as the layer- 2  LH compressed data  152 . In a similar manner, upon the reception of the layer- 2  HH data  1054  and the layer-O HH significance attribute data  162 , the layer- 2  HH significance attribute addition module  106  generates a copy of the layer- 2  HH data  1054  as the layer- 2  HH compressed data  153 . 
     Upon the reception of the compressed data  151 - 153 ,  1067 - 1069 ,  1063 - 1065  of the individual layers except for the significance attribute, the insignificant-space-estimation deletion unit  107  performs the data compression by deleting the insignificant spaces. Thereby, the compressed data (i.e., the layer- 1  HL compressed data  154 , layer- 1  LH compressed data  155 , layer- 1  HH compressed data  156 , layer- 0  HL compressed data  157 , layer- 0  LH compressed data  158 , and the layer- 0  HH compressed data  159 ) are generated. At the same time, the insignificant-space-estimation deletion unit  107  generates the insignificance decision signal  163  of the layer- 2  for the addition of the significance attribute. The deletion of the insignificant spaces is carried out in the manner described below. 
     In FIG. 2, the insignificant space estimation module  301  receives the layer- 2  HL compressed data  151  (layer- 2  HL) to perform the threshold value decision. Thereby, the minimum-value-area-estimation in the data of the one-rank lower layer succeeding to the layer- 2  HL compressed data  151  (i.e., the layer- 1  HL data  1067 ) is performed to generate the layer- 1  HL insignificant space estimation data  351 . Through the similar procedure, the insignificant space estimation modules  302  and  303  receive the component wavelet compressed data of the layer- 2  (i.e., the layer- 2  LH compressed data  152  and the layer- 2  HH compressed data  153 ) to perform the minimum-value-area estimation in the data of the one-rank lower layer. Thereby, the layer- 1  LH insignificant space estimation data  352  and the layer- 1  HH insignificant space estimation data  353  are generated. Then, the estimation-result logical-ORing module  304  performs the logical ORing operation on the layer- 1  HL insignificant space estimation data  351 , the layer- 1  LH insignificant space estimation data  352  and the layer- 1  HH insignificant space estimation data  353  as received. Thereby, an insignificance decision signal  163  indicating the event of data deletion through the insignificant space prediction is generated. 
     Subsequently, upon the reception of the layer- 1  HL insignificant space estimation data  351  and the layer- 1  HL data  1067 , the layer- 1  HL deletion module  1204  deletes data of the insignificance-estimated area to generate the layer- 1  HL compressed data  154 . Likewise, the layer- 1  LH compressed data  155  and the layer- 1  HH compressed data  156  are generated on the basis of the layer- 1  LH data  1068  and the layer- 1  HH data  1069  as well as the layer- 1  LH insignificant space estimation data  352  and the layer- 1  HH insignificant space estimation data  353 . 
     The insignificant space estimation modules  1207 - 1209  receives the layer- 1  compressed data  154 - 156  to perform the minimum-value-area estimation in the data in the one-rank lower layer (i.e., the layer- 0 ). Thereby, the insignificant space estimation data  354 - 356  are generated. 
     In succession, upon the reception of the layer- 0  HL insignificant space estimation data  354  and the layer- 0  HL data  1063 , the layer- 0  HL insignificant space deletion module  1210  deletes data in the insignificance-estimated area to generate the layer- 0  HL compressed data  157 . Similarly, the compressed data  158  and  159  of the layer- 0  are generated on the basis of the layer- 0  LH data  1064  and the layer- 0  HH data  1065  as well as the insignificant space estimation data  355  and  356  of the layer- 0 . Thereby, the insignificant spaces in the wavelet data are deleted. Through the operations described above, the compression of the image data can be accomplished. 
     The insignificance decision signal  163  generated by the insignificant-space-estimation deletion unit  107  is supplied to error-estimation detection modules  101 - 103  of the layer- 0 . In FIG. 1, upon the reception of the insignificance decision signal  163  and the layer- 0  HL data  1063 , the layer- 0  HL error-estimation detection module  101  performs the detection of the significant data in the insignificance-estimated space. Thereby, the layer- 0  HL significance attribute data  160  is generated. Likewise, upon the reception of the insignificance decision signal  163  and the layer- 0  LH data  1064 , the layer- 0  LH error-estimation detection module  102  performs the detection of the significant data in the insignificance-estimated space. Thereby, the layer- 0  LH significance attribute data  161  is generated. In a similar manner, upon the reception of the insignificance decision signal  163  and the layer- 0  HH data  1065 , the layer- 0  HH error-estimation detection module  103  performs the detection of the significant data in the insignificance-estimated space. Thereby, the layer- 0  HH significance attribute data  162  is generated. 
     At this juncture, description will be made of the operation for detecting the significant data in the insignificance-estimated space by taking as example the operation of the layer- 0  HL error-estimation detection module  101 . When the value of the layer- 0  HL data  1063  is not smaller than a given threshold value and when the insignificance decision signal  163  indicates that an insignificant space has been estimated, then data fault is decided. Thereby, the layer- 0  HL significance attribute data  160  is asserted (decided to be active). FIG. 3 is a view for illustrating the detection of the significant data in the significance-estimated space and the addition of the significance attribute. 
     The layer- 0  HL significance attribute data  160  and the layer- 2  HL data  1052  are received by the layer- 2  HL significant attribute addition module  104 . In that case, if the layer- 0  HL significance attribute data  160  has been asserted (decided to be active), then the layer- 2  HL significant attribute addition module  104  generates the layer- 2  HL compressed data  151  affixed with the significance attribute by adding the significance attribute to the layer- 2  HL data  1052 . In FIG. 3, hatched areas of the layer- 0  HL significance attribute data  160  represent the asserted portions thereof. 
     Through the similar procedure, the layer- 2  LH significance attribute addition module  105  receives the layer- 0  LH significance attribute data  161  and the layer- 2  LH data  1053  to generate the layer- 2  LH compressed data  152 . The layer- 2  HH significance attribute addition module  106  receives the layer- 0  HH significance attribute data  162  and the layer- 2  HH data  1054  to generate the layer- 2  HH compressed data  153 . With the above-mentioned operation, the image data is compressed. 
     Next, description will be directed to the decoding processing by reference to FIG.  4 . When the compressed data  151 - 159  and  1501  of the individual layers are supplied, the insignificant-space-estimation development unit  201  performs the decoding of the data compressed by deleting the insignificant spaces. Thereby, the layer- 1  HL expanded data  256 , the layer- 1  LH expanded data  257 , the layer- 1  HH expanded data  258 , the layer- 0  HL expanded data  260 , the layer- 0  LH expanded data  261  and the layer- 0  HH expanded data  262  are generated. 
     Now, description will turn to the decode processing of the data compressed by the deletion of the insignificant space. FIG. 5 is a block diagram showing a structure of the insignificant-space-estimation development unit  201 . In FIG. 5, upon the reception of the layer- 2  HL compressed data  151 , the insignificant space prediction module  301  estimates the minimum value area in the layer- 2  HL wavelet space  1609  on the basis of the threshold value and the significance attribute. Thereby, the layer- 1  HL insignificant space development estimation data  451  is generated. Similarly, upon the reception of the layer- 2  LH compressed data  152  and the layer- 2  HH compressed data  153 , the insignificant space estimation module  302  and the insignificant space estimation module  303  generate the layer- 1  LH insignificant space development estimation data  452  and the layer- 1  HH insignificant space development estimation data  453 , respectively. 
     Upon the reception of the layer- 1  HL insignificant space development estimation data  451  and the layer- 1  HL compressed data  154 , the layer- 1  HL development module  1301  embeds the minimum value in the insignificance-estimated area to generate the layer- 1  HL expanded data  256 . Similarly, upon the reception of the layer- 1  LH insignificant space development estimation data  452  and the layer- 1  LH compressed data  155 , the layer- 1  LH development module  1302  embeds the minimum value in the insignificance-estimated area to generate the layer- 1  LH expanded data  257 . Upon the reception of the layer- 1  HH insignificant space development estimation data  453  and the layer- 1  HH compressed data  156 , the layer- 1  HH development module  1303  embeds the minimum value in the insignificance-estimated area to generate the layer- 1  HH expanded data  258 . 
     Upon the reception of the layer- 1  HL expanded data  256 , the insignificant space estimation module  1207  performs the minimum-value-area estimation in the layer- 1  HL wavelet space  1606  through the threshold value decision to generate the layer- 0  HL insignificant space development estimation data  454 . Likewise, upon the reception of the layer- 1  LH expanded data  257 , the insignificant space estimation module  1208  generates the layer- 0  LH insignificant space development estimation data  455 . Upon the reception of the layer- 1  HH expanded data  258 , the insignificant space estimation module  1209  generates the layer- 0  HH insignificant space development estimation data  456 . 
     Upon the reception of the layer- 0  HL insignificant space development estimation data  454  and the layer- 0  HL compressed data  157 , the layer- 0  HL development module  1304  fills the insignificance-estimated area with the minimum value to generate the layer- 0  HL expanded data  260 . Similarly, upon the reception of the layer- 0  LH insignificant space development estimation data  455  and the layer- 0  LH compressed data  158 , the layer- 0  LH development module  1305  generates the layer- 0  LH expanded data  261  to perform the decoding of the wavelet data. Upon the reception of the layer- 0  HH insignificant space development estimation data  456  and the layer- 0  HH compressed data  159 , the layer- 0  HH development module  1306  generates the layer- 0  HH expanded data  262  to perform the decoding of the wavelet data. 
     Referring to FIG. 4, the HL significance attribute separating module  202  receives the layer- 2  HL compressed data  151  to generate the layer- 2  HL significance-attribute-estimated data  252  (i.e., the data from which the significance attribute has been deleted). Similarly, the LH significance attribute separating module  203  receives the layer- 2  LH compressed data  152  to generate the layer- 2  LH significance-attribute-estimated data  253 . The HH significance attribute separating module  204  receives the layer- 2  HH compressed data  153  to generate the layer- 2  HH significance-attribute-estimated data  254 . 
     The layer- 0  subband synthesis unit  1102  receives the layer- 2  wavelet data (i.e., the layer- 2  DC data  1051 , layer- 2  HL significance-attribute-estimated data  252 , layer- 2  LH significance-attribute-estimated data  253  and the layer- 2  HH significance-attribute-estimated data  254 ) to perform the reverse wavelet transformation. Thereby, the layer- 1  DC expanded data  255  is generated. The layer- 1  subband synthesis unit  1103  receives the layer- 1  wavelet data (i.e., the layer- 1  DC expanded data  255 , layer- 1  HL expanded data  256 , layer- 1  LH expanded data  257  and the layer- 1  HH expanded data  258 ) to perform the reverse wavelet transformation. Thereby, the layer- 0  DC expanded data  259  is generated. The layer- 2  subband synthesis unit  1104  receives the layer- 0  wavelet data (i.e., the layer- 0  DC expanded data  259 , layer- 0  HL expanded data  260 , layer- 0  LH expanded data  261  and layer- 0  HH expanded data  262 ) to perform the reverse wavelet transformation. Thereby, the expanded image data  251  is generated. 
     With the processing described above, the expansion of the image data can be accomplished. 
     As will now be understood from the foregoing description, the image data processing method and the image data processing system according to the present invention are arranged in the following manner. Upon the prediction of the space in which the significant data of the high-frequency data after the subband division exists, when some significant data exists in the space estimated as the insignificant space, the significance indicating attribute is affixed to the insignificance-decided space corresponding to the space in which the significant data exists, and the insignificant space to be compressed is re-estimated on the basis of the threshold value and the significance attribute of the insignificance-decided space affixed with the significance attribute. Thereby, it is possible to delete the insignificant space in the high-frequency data with high accuracy, to impart the positive correlation to the wavelet transformed data having no correlation to the frequency direction, and to predict the significant space of the high frequency with high accuracy on the basis of the frequency correlation. Thus, the insignificant area can be estimated with the enhanced estimation accuracy, which in turn makes it possible to compress the image data effectively and efficiently while protecting the image quality against degradation or deterioration. 
     Many features and advantages of the present invention are apparent from the detailed description and thus it is intended by the appended claims to cover all such features and advantages of the method and the system which fall within the true spirit and scope of the invention. Further, since numerous modifications and combinations will readily occur to those skilled in the art, it is not intended to limit the invention to the exact construction and operation illustrated and described. Accordingly, all suitable modifications and equivalents may be resorted to, falling within the spirit and scope of the invention.