JP3576812B2 - Image processing apparatus and image processing method - Google Patents

Description

そして、ファインスキャンデータＳ_Ｆ から低周波数成分Ｒ_Ｌ 、Ｇ_Ｌ 、Ｂ_Ｌ を減算して中間高周波数成分Ｒ_ＭＨ、Ｇ_ＭＨ、Ｂ_ＭＨを抽出する。前記抽出された後の低周波数成分Ｒ_Ｌ 、Ｇ_Ｌ 、Ｂ_Ｌ は、カラー画像中のエッジや細かいテクスチャやフィルムの粒状によるザラツキを含まないものである。一方、中間周波数成分Ｒ_Ｍ 、Ｇ_Ｍ 、Ｂ_Ｍ はフィルム粒状によるザラツキを含むものであり、高周波数成分Ｒ_Ｈ 、Ｇ_Ｈ 、Ｂ_Ｈ は、カラー画像中のエッジや細かいテクスチャーを含むものである。
【００６５】
ここで、ファインスキャンデータの低周波数成分Ｒ_Ｌ 、Ｇ_Ｌ 、Ｂ_Ｌ 、中間周波数成分Ｒ_Ｍ 、Ｇ_Ｍ 、Ｂ_Ｍ 及び高周波数成分Ｒ_Ｈ 、Ｇ_Ｈ 、Ｂ_Ｈ とは図１３に示すように分布される中間・高周波数成分に乗じるゲインＭ、Ｈを１．０とした場合の周波数成分のことをいう。また、中間周波数成分Ｒ_Ｍ 、Ｇ_Ｍ 、Ｂ_Ｍ は、処理後のデータを可視像として再生する際の出力のナイキスト周波数ｆｓ／２の１／３付近にピークを持って分布Ｈ_Ｍ となる周波数成分をいう。さらに低周波数成分Ｒ_Ｌ 、Ｇ_Ｌ 、Ｂ_Ｌ とは、０周波数にピークを持って分布Ｈ_Ｌ となる成分をいい、高周波数成分Ｒ_Ｈ 、Ｇ_Ｈ 、Ｂ_Ｈ とは、出力のナイキスト周波数ｆｓ／２にピークを持って分布Ｈ_Ｈ となる成分をいう。
【００６６】
なお、本実施の形態において、ナイキスト周波数は、感光材料への記録が３００ｄｐｉで行われる場合のナイキスト周波数をいうものである。ここで図６においては、各周波数において周波数成分の和は１となっている。
【００６７】
ついで分解された中間・高周波数成分Ｒ_ＭＨ、Ｇ_ＭＨ、Ｂ_ＭＨから輝度成分が抽出される。この輝度成分の抽出はファインスキャンデータの中間・高周波数成分Ｒ_ＭＨ、Ｇ_ＭＨ、Ｂ_ＭＨをＹＩＱ基底に変換した際の成分Ｙ_ＭＨがデータの輝度成分を表すものである。ここでＹＩＱ基底への変換は下記の式により行う。
【００６８】
【数２】

ＹＩＱ基底に変換後の色成分である成分Ｉ_ＭＨ及び成分Ｑ_ＭＨはフィルム粒状に起因する色のザラツキを含むものであるため、成分Ｉ_ＭＨ及び成分Ｑ_ＭＨはここでは０とおいてフィルム粒状に起因する色のザラツキを抑制する。
【００６９】
ここで、色成分である成分Ｉ_ＭＨ及び成分Ｑ_ＭＨは一般の被写体を写した画像の場合は殆ど成分を持たないことが経験的にわかっている。したがって、成分Ｉ_ＭＨ及び成分Ｑ_ＭＨは、フィルム粒状に起因する色のザラツキとみなして０とおくことにより、ザラツキを抑制した良好な再生画像を得ることができる。
【００７０】
ついで、成分Ｙ_ＭＨに対してゲイン処理部において上述した５×５のローパスフィルタによりフィルタリング処理を施して、成分Ｙ_ＭＨの中間周波数成分Ｙ_Ｍ を得る。さらに、成分Ｙ_ＭＨから中間周波数成分Ｙ_Ｍ を減算することにより成分Ｙ_ＭＨの高間周波数成分Ｙ_Ｈ を得る。
【００７１】
次いで、前述した粒状度補正・シャープネス補正部２２０において求められたゲインＭ及び、ゲインＨが以下の式に示すように、それぞれ成分Ｙ_Ｍ 、Ｙ_Ｈ に乗じられて処理済成分Ｙ_Ｍ ’ 、Ｙ_Ｈ ’ が得られ、処理済成分Ｙ_Ｍ ’ 、Ｙ_Ｈ ’ が合成されて成分Ｙ_ＭＨ’ が得られる。
【００７２】
Ｙ_ＭＨ’ ＝ゲインＭ×Ｙ_Ｍ ＋ゲインＨ×Ｙ_Ｈ …式（３）
（Ｙ_Ｍ ’ ＝ゲインＭ×Ｙ_Ｍ 、Ｙ_Ｈ ’ ＝ゲインＨ×Ｙ_Ｈ ）
ここで、ゲインＭと、ゲインＨとは粒状度補正・シャープネス補正部２２０においてゲインＭ＜ゲインＨとなるように設定される。すなわち、フィルム粒状に基づく輝度成分のザラツキは、中間周波数成分に比較的多く含まれているため、成分Ｙ_Ｍ のゲインＭを比較的低く設定することより、ザラツキ感を抑えることができる。また、画像のシャープネス度合いは輝度成分の高周波数成分に依存するため、輝度成分の高周波数成分Ｙ_Ｈ のゲインＨを比較的大きくすることにより、処理済画像の鮮鋭度を強調することができる。
【００７３】
例えば、カラー画像がアンダーネガの場合、フィルム粒状に起因するザラツキが目立つ上に階調特性を改善するために階調を立ると、粒状がかなり悪い画像となるため、単位領域毎に算出されるゲインＭをかなり低く設定することにより、粒状を強く抑制できる。
【００７４】
すなわち、粒状度補正・シャープネス補正部２２０においては、上述した方法により分割した領域毎に最も適したゲインＭを補正量として算出し、このゲインＭに基づいて粒状度を抑制している。このゲインＭは、分割した画像データの面積に応じて設定したり、ユーザの好みに応じたゲインＧ及びゲインＨをテーブルとして記憶しておき、ユーザの選択に応じたゲインＧ及びゲインＨを単位領域１００毎に適宜選択するように構成することもできる。
【００７５】
そして、このようにして得られた成分Ｙ_ＭＨ’ を前述したファインスキャンデータＳ_Ｆ の低周波数成分Ｒ_Ｌ 、Ｇ_Ｌ 、Ｂ_Ｌ と合成して処理済信号Ｒ’、Ｇ’、Ｂ’を得る。この際、前述した成分Ｉ_ＭＨ’を逆変換してＲＧＢのデータに対応させると、ＲＧＢ３つのデータは全て成分Ｙ_ＭＨ’と同一の値となるので、処理された輝度成分_ＭＨ’を逆変換しないで合成することより処理を簡便なものとできる。
【００７６】
その後、以上の処理を単位領域１００毎に行って、単位領域１００毎に得られた複数の処理済信号Ｒ’、Ｇ’、Ｂ’をそれぞれ画像データ変換部２１０に出力する。
【００７７】
【発明の効果】
以上説明したように、本発明によれば、１コマの画像データの粒状度補正を部分的な画像データに基づいて行うため、１コマ内に写し込まれた画像において粒状度の違いに応じてきめ細かい補正が可能な画像処理装置が得られる、という効果を達成する。
【図面の簡単な説明】
【図１】本発明の実施の形態にかかるデジタルラボシステムの概略構成図である。
【図２】デジタルラボシステムの概観図である。
【図３】画像処理部の制御ブロック図である。
【図４】１コマ分の画像データを９×５の単位領域１００毎に分割した状態を示す説明図である。
【図５】濃度と色（輝度）の相関関係を示す線図である。
【図６】色（輝度）と粒状度の補正量との相関関係を示す線図である。
【図７】１コマ分の画像データを左側領域１０２と中央領域１０４と右側領域１０６に３分割した状態を示す説明図である。
【図８】１コマ分の画像データを中心領域１１０とその他の領域１０８とに分割した状態を示す説明図である。
【図９】１コマ分の画像データを主要被写体抽出手段により画像データから主要被写体１２０のみを抽出して所要被写体１２０とその他の領域１０８とに分割した状態を示す説明図である。
【図１０】１コマ分の画像データを９×５に分割し、主要被写体が映り込んだ６領域とその他の領域とに分割した状態を示す説明図である。
【図１１】１コマ分の画像データから算出した濃度累積ヒストグラムの一例を示す線図である。
【図１２】本実施形態に係る粒状抑制、シャープネス強調処理の一例を示すブロック図である。
【図１３】低周波数成分、中間周波数成分、高周波数成分の分布を示す特性図である。
【符号の説明】
１０ ディジタルラボシステム
１４ ラインＣＣＤスキャナ
１６ 画像処理部
６６ 光源部
６８ 写真フィルム
２００ データ処理部
２０２ ｌｏｇ 変換器
２０４ プレスキャンメモリ
２０６ メインスキャンメモリ
２０８ 画像データ処理部
２１２ プレスキャン処理部
２１４ 画像データ処理部
２１８ メインスキャン処理部
２２０ 粒状度補正・シャープネス補正部
２２４ 条件設定部
２３４ レンズ特性データ供給部[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to an image processing apparatus, and more particularly to an image processing apparatus that performs predetermined image processing on image data obtained by photoelectrically reading an image recorded on a film to obtain image data for output.
[0002]
[Prior art]
In recent years, a frame image recorded on a photographic film is photoelectrically read by a reading sensor such as a CCD, and image processing such as enlargement / reduction and various corrections is performed on digital image data obtained by the reading, and the image processing is completed. A technique for forming an image on a recording material using a laser beam modulated based on digital image data is known.
[0003]
As described above, in the technology of digitally reading a frame image using a reading sensor such as a CCD, in order to realize accurate image reading, the frame image is preliminarily read (so-called pre-scan), and the density of the frame image is adjusted according to the density. Reading conditions (for example, the amount of light applied to the frame image and the charge storage time of the CCD) are determined, and the frame image is read again under the determined reading conditions (so-called fine scan).
[0004]
At the time of prescan, correction values corresponding to various correction processes such as color gradation, hypertone, hypersharpness, and granularity are detected based on the read image, and fine scan is performed based on the obtained correction values. Has been subjected to correction processing.
[0005]
The granularity, which is one of the correction processing targets, refers to the degree of roughness or roughness of the image of the film, and the higher the granularity, the finer the image. The granularity may indicate a degree relative to a predetermined reference film, or may indicate a relative degree in one image in the same film.
[0006]
Granularity is one of the important factors that determine the quality of an image, and correction of the granularity is performed, for example, as disclosed in JP-A-63-272173, before color negative film reversal processing is performed. The exposure state is determined for each frame image, and the granularity corresponding to each frame screen is variably corrected based on the exposure state for each frame image obtained by this determination.
[0007]
[Problems to be solved by the invention]
However, in the above-described granularity correction method, since the correction value detected according to whether the exposure state of the image projected in one frame is under or over is applied to the entire image, the correction value is partially excessive in one frame. There is a drawback in that a corrected area is generated, and conversely, an undercorrected area is generated.
[0008]
Therefore, an object of the present invention is to provide an image processing apparatus and an image processing method capable of performing fine correction in accordance with a difference in granularity in an image printed in one frame.
[0009]
[Means for Solving the Problems]
In order to achieve the first object, an image processing apparatus according to the first aspect of the present invention performs predetermined image processing on image data obtained by photoelectrically reading an image recorded on a film, and outputs the image data for output. A granularity correction amount calculation unit that calculates a granularity correction amount for each predetermined region based on respective densities of a plurality of predetermined regions formed by dividing the image data. Means for correcting the granularity of the image data based on the correction amount for each predetermined area calculated by the granularity correction amount calculating means, and reflecting the correction amount in a sharpness enhancement process for the image data. Granularity correction means.
[0010]
According to the first aspect of the invention, instead of calculating the granularity correction amount based on the exposure state of the entire image (hereinafter, referred to as an image of one frame) imprinted on one frame, The image data of the image for one frame is divided into each predetermined area, and the granularity correction amount calculating means calculates the correction amount of the granularity for each predetermined area, and the granularity correction is performed based on the obtained correction amount. The means reflects the correction amount in the sharpness enhancement processing for the image data, and corrects the granularity of the image data. That is, since the granularity can be corrected in consideration of the partial image density (a plurality of densities) in one frame image, fine granularity correction can be realized.
Further, since the correction amount of the granularity is reflected in the sharpness enhancement processing for adjusting the sharpness enhancement degree having a trade-off relationship with the granularity, excessive granularity correction can be suppressed.
For example, the gain of high-frequency components including edges and fine textures in a color image is made relatively large to emphasize sharpness, and the gain of intermediate frequency components including graininess due to film grain in image data is made relatively small to achieve graininess. By correcting the degree, the roughness can be suppressed while enhancing the sharpness of the image.
[0011]
In the first aspect, the method of dividing the image data of one frame of image into each predetermined area is not particularly limited. For example, the method may be such that the image data is divided evenly in a grid pattern or in a honeycomb shape centered on the center. The optimal division method can be selected as appropriate, such as dividing the image into a radial portion, a concentric shape, or a combination thereof, or dividing the image into a central portion where the main subject is most likely to be arranged and other portions.
[0014]
According to a second aspect of the present invention, in the image processing apparatus according to the first aspect, the granularity correction unit corrects the image data for each predetermined area based on a correction amount corresponding to each predetermined area. .
[0015]
That is, according to the second aspect of the present invention, the granularity correction of each corresponding predetermined area is performed based on the correction amount calculated for each predetermined area obtained by dividing one frame of image. Thus, different degrees of granularity correction can be realized, and the granularity correction can be performed finely in accordance with an image for one frame.
[0016]
According to a third aspect of the present invention, in the image processing apparatus according to the first aspect, the granularity correction unit determines the position of the predetermined position based on a correction amount calculated from a predetermined area of the predetermined position. Only the image data in the predetermined area is corrected.
[0017]
That is, in the third aspect of the present invention, the correction amount of the granularity in one predetermined area or a plurality of predetermined areas is obtained from each of the predetermined areas obtained by dividing one frame of the image, and the predetermined amount is determined. Since only the image data of one predetermined area or a plurality of predetermined areas is corrected, the granularity can be partially corrected in an image for one frame.
[0018]
When a plurality of predetermined regions are selected, a correction amount of granularity is obtained for each predetermined region to correct the corresponding image data, or a correction amount of granularity is obtained for each predetermined region. It is preferable to correct the image data of the entire plurality of predetermined regions in accordance with the most appropriate correction amount among them, or to obtain the correction amount of the granularity of the entire plurality of predetermined regions to obtain the image data of the entire plurality of predetermined regions. Can be corrected.
[0019]
Therefore, for example, after performing the granularity correction on the entire image of one frame based on the exposure state as in the related art, only the predetermined area in the overcorrected state or the undercorrected state is selected to further perform the granularity correction. Can be performed, and a finer granularity correction process can be realized.
[0020]
Of course, it is also possible to select only a predetermined area at a specific position of one frame of the image before performing the granularity correction, and to perform the granularity correction only on the selected area, and the quality of the image data to be corrected It is possible to change the granularity correction method according to the conditions.
[0021]
According to a fourth aspect of the present invention, in the image processing apparatus according to the first aspect, the predetermined area is an area composed of one pixel. That is, the granularity can be corrected most finely by forming the predetermined area with one pixel.
[0022]
Further, according to a fifth aspect of the present invention, in the image processing apparatus according to the first aspect, the image processing apparatus further includes a main subject extracting unit that extracts an occupied area of the main subject from the image data, and the predetermined area is the main subject extracting unit. Or the area other than the occupied area extracted by the above.
[0023]
Accordingly, the correction amount of the main part in the image can be appropriately obtained in accordance with the image printed on each frame, so that the granularity can be finely corrected in accordance with the image.
[0024]
According to a sixth aspect of the present invention, in the image processing apparatus according to the first aspect, the predetermined area is a set of pixels of a specific density obtained from a density cumulative histogram of the image data.
[0025]
That is, since the granularity is better in the high density area in the image data than in the low density area, the granularity is adjusted according to the density of the main part in the image obtained from the density cumulative histogram of the image data. By changing the correction amount, it is possible to prevent the granularity from being locally deteriorated due to the density difference in the image data for one frame.
[0026]
According to a seventh aspect of the present invention, in the image processing apparatus according to any one of the first to sixth aspects, the density is a relative density difference from an applied film base density. Thereby, even if the film uses a different film base, an appropriate correction amount of the granularity can always be calculated.
[0027]
The reference granularity correction condition differs depending on, for example, a difference between a negative film or a reversal film, a difference between film sensitivities, and a difference between film types. Therefore, in the invention according to claim 8 , in the image processing apparatus according to any one of claims 1 to 7 , the image processing apparatus further includes a film type determination unit that determines a film type, and the granularity correction amount calculation unit includes: A reference value for calculating a correction amount is adjusted in accordance with the film type from the film type determination means.
[0028]
Accordingly, the reference granularity correction condition can be adjusted in accordance with the type of the film to be corrected, so that the granularity can be more finely corrected.
On the other hand, in order to achieve the above object, the image processing method according to the ninth aspect of the present invention performs predetermined image processing on image data obtained by photoelectrically reading an image recorded on a film, and outputs the image data for output. An image processing method for obtaining image data, wherein a correction amount of granularity for each predetermined region is calculated based on each density of a plurality of predetermined regions formed by dividing the image data. Based on the correction amount for each predetermined area, the granularity of the image data is corrected, and the correction amount is reflected in sharpness enhancement processing on the image data.
According to the ninth aspect of the present invention, since it operates in the same manner as the first aspect of the present invention, similar to the first aspect of the present invention, the difference in granularity between images captured in one frame is reduced. Detailed correction can be performed accordingly.
[0029]
DETAILED DESCRIPTION OF THE INVENTION
1 and 2 show a schematic configuration of a digital laboratory system 10 according to the present embodiment.
[0030]
As shown in FIG. 1, the digital lab system 10 includes a line CCD scanner 14, an image processing unit 16, a laser printer unit 18, and a processor unit 20. Are integrated as an input unit 26 shown in FIG. 2, and the laser printer unit 18 and the processor unit 20 are integrated as an output unit 28 shown in FIG.
[0031]
The line CCD scanner 14 is for reading a frame image recorded on a photographic film such as a negative film or a reversal film, and includes, for example, a 135-size photographic film, a 110-size photographic film, and a transparent magnetic layer. It is possible to read a frame image of a photographic film (240-size photographic film: so-called APS film) or a photographic film of 120-size or 220-size (Brownie size). The line CCD scanner 14 reads the above-mentioned frame image to be read by the line CCD 30, performs A / D conversion in the A / D conversion unit 32, and outputs image data to the image processing unit 16.
[0032]
In the present embodiment, a digital lab system 10 in which a 240-size photographic film (APS film) 68 is used will be described.
[0033]
The image processing unit 16 receives image data (scanned image data) output from the line CCD scanner 14 and scans image data obtained by photographing with the digital camera 34 or the like and a document (for example, a reflection document). 36 (flatbed type), image data generated by another computer and recorded in a floppy disk drive 38, MO drive or CD drive 40, and communication received via a modem 42 Image data and the like (hereinafter, these are collectively referred to as file image data) can be input from the outside.
[0034]
The image processing unit 16 stores the input image data in the image memory 44, and performs image processing such as various corrections of a color gradation processing unit 46, a hypertone processing unit 48, a hyper sharpness processing unit 50, and the like. The image data is output to the laser printer unit 18 as image data for recording. Further, the image processing unit 16 outputs the image data on which the image processing has been performed to an external device as an image file (for example, outputs the image data to a storage medium such as an FD, an MO, a CD, or to another information processing device via a communication line). Transmission, etc.).
[0035]
The laser printer section 18 includes R, G, and B laser light sources 52, and controls a laser driver 54 to record image data input from the image processing section 16 (temporarily stored in the image memory 56). The printing paper 62 is irradiated with laser light modulated in accordance with the above, and an image is recorded on the printing paper 62 by scanning exposure (in the present embodiment, mainly an optical system using the polygon mirror 58 and the fθ lens 60). Further, the processor unit 20 performs each process of color development, bleach-fixing, washing, and drying on the photographic paper 62 on which the image is recorded by the scanning exposure by the laser printer unit 18. Thus, an image is formed on the printing paper.
[0036]
(Configuration of line CCD scanner)
Next, the configuration of the line CCD scanner 14 will be described. FIG. 1 shows a schematic configuration of an optical system of the line CCD scanner 14. This optical system includes a light source 66 for irradiating the photographic film 68 with light, and a light diffusing plate 72 for diffusing the light to irradiate the photographic film 68 is disposed on the light exit side of the light source 66. .
[0037]
The photographic film 68 is conveyed by a film carrier 74 disposed on the side where the light diffusion plate 72 is disposed so that the screen of the frame image is perpendicular to the optical axis.
[0038]
On the opposite side of the photographic film 68 from the light source 66, a lens unit 76 for imaging light transmitted through the frame image and the line CCD 30 are sequentially arranged along the optical axis. Although only a single lens is shown as the lens unit 76, the lens unit 76 is actually a zoom lens composed of a plurality of lenses. Note that a selfoc lens may be used as the lens unit 76. In this case, it is preferable that both end surfaces of the SELFOC lens be as close to the photographic film 68 and the line CCD 30 as possible.
[0039]
The line CCDs 30 are arranged in a line along the width direction of the photographic film 68 conveyed by a plurality of CCD cells, and three sensing units provided with an electronic shutter mechanism are provided in parallel with each other at intervals. Each of the R, G, and B color separation filters is attached to the light incident side of each sensing unit (a so-called three-line color CCD). The line CCD 30 is arranged so that the light receiving surface of each sensing unit coincides with the imaging point position of the lens unit 76.
[0040]
Although not shown, a shutter is provided between the line CCD 30 and the lens unit 76.
[0041]
(Configuration of control system of image processing unit 16)
FIG. 3 is a detailed control block diagram for executing each processing of the image memory 44, the color gradation processing 46, the hypertone processing 48, and the hypersharpness processing 50, which are the main components of the image processing unit 16 shown in FIG. It is shown.
[0042]
Each of the RGB digital signals output from the line CCD scanner 14 is subjected to predetermined data processing such as darkness correction, defective pixel correction, and shading correction in a data processing unit 200, and then converted to a digital image by a log converter 202. The data is converted into data (density data), the pre-scan data is stored in the pre-scan memory 204, and the main scan data is stored in the main scan memory 206.
[0043]
The pre-scan data stored in the pre-scan memory 204 is sent to a pre-scan processing unit 212 including an image data processing unit 208 and an image data conversion unit 210. On the other hand, the main scan data stored in the main scan memory 206 is sent to a main scan processing unit 218 including an image data processing unit 214 and an image data conversion unit 216.
[0044]
The pre-scan processing unit 212 and the main scan processing unit 218 execute correction based on the lens characteristics at the time of shooting an image and the strobe light distribution characteristics at the time of shooting using a strobe.
[0045]
Further, the image data processing units 208 and 214 acquire film characteristic storage unit 232 for storing characteristics of various films, acquire information for identifying a camera that has photographed the film, and output lens characteristics according to the corresponding photographing camera. Connected to a lens characteristic data supply unit 234.
[0046]
The characteristic of the film is a gradation characteristic (γ characteristic), which is generally represented by a curve whose density changes three-dimensionally in accordance with the amount of exposure. Since this point is a well-known technique, detailed description will be omitted.
[0047]
In the present embodiment, the film type is specified by recording information indicating the film type on the magnetic recording layer of the APS film, and is read by a magnetic head when the line CCD scanner 14 is transported by the carrier 74. It is possible. In the case of a 135-size film, the determination may be made based on the shape (perforations are provided at relatively short pitches at both ends in the width direction) or the like, or an operator may make a key input. By specifying the film type, the relative density of the image from the film base density can be accurately calculated.
[0048]
The image data processing units 208 and 214 correct the reference value according to the film type and the camera type obtained from the film characteristic storage unit 232 and the lens characteristic data supply unit 234, and use an LUT, a matrix (MTX) operation, or the like. By a known method, parameters for color balance adjustment, contrast adjustment (color gradation processing), brightness correction, saturation correction (hypertone processing), and the like are obtained.
[0049]
Further, the image data processing units 208 and 214 calculate the granularity correction amount for each unit area 100 based on the respective densities of a plurality of unit areas (predetermined areas) 100 formed by dividing one frame of image data. A granularity correction / sharpness correction unit 220 that calculates and determines the degree of sharpness and corrects the degree of granularity and the degree of sharpness according to the calculated correction amount of granularity (granularity correction amount calculating means, granularity correcting means) The granularity correction / sharpness correction unit 220 calculates a correction amount for performing a granularity correction process by a process described later.
[0050]
The prescan-side image data conversion unit 210 converts the plurality of image data obtained for each unit area 100 by the image data processing unit 208 into display image data to be displayed on the monitor 16M based on the 3D-LUT. ing. On the other hand, the image data conversion unit 216 on the main scan side converts the image data processed by the image data processing unit 214 into image data for printing in the laser printer unit 18 based on the 3D-LUT. Although the display image data and the print image data have different color systems, they are matched by various corrections as described below.
[0051]
That is, the condition setting unit 224 is connected to the pre-scan processing unit 212 and the main scan processing unit 218. The condition setting unit 224 includes a setup unit 226, a key correction unit 228, and a parameter integration unit 230.
[0052]
The setup unit 226 sets the main scan reading conditions using the pre-scan data, supplies the main scan reading conditions to the line CCD scanner 14, and calculates the image processing conditions of the pre-scan processing unit 212 and the main scan processing unit 218. The parameter is supplied to the parameter integration unit 230.
[0053]
The key correction unit 228 adjusts image processing conditions in accordance with keys set on the keyboard 16K for adjusting density, color, contrast, sharpness, saturation, granularity, and the like, and various instructions input with a mouse. Is calculated and supplied to the parameter integration unit 230.
[0054]
The parameter integration unit 230 sends the image processing conditions received from the setup unit 226 and the key correction unit 228 to the image data processing units 208 and 214 on the prescan side and the main scan side, and corrects or resets the image processing conditions.
[0055]
Here, processing performed in the granularity correction / sharpness correction unit 220 will be described. The granularity correction / sharpness correction unit 220 divides the prescan data into one frame of image data for each 9 × 5 unit area 100 as shown in FIG. Then, the correction amount of the granularity is determined based on the calculated density.
[0056]
FIG. 5 is a diagram showing the correlation between the color (luminance) and the density. As shown in FIG. 5, the color (luminance) and the density are not in a proportional relationship but in a quadratic curve relationship. Also, the lower the density, the worse the granularity becomes, and the image becomes more conspicuous. From these facts, the color (luminance) and the correction amount of the granularity have a curve relationship as shown in FIG. 6, and the correction amount of the granularity increases as the color (luminance) decreases.
[0057]
The granularity correction / sharpness correction unit 220 of the present embodiment calculates the average density for each unit area 100, obtains the luminance from the obtained average density based on the diagram shown in FIG. The correction amount of the granularity is calculated for each unit area 100 based on the illustrated diagram.
[0058]
Here, one frame of image data is divided into 9 × 5 unit areas 100, but the division method is not limited to 9 × 5, but may be 6 × 6, 10 × 10, pixel by pixel, or the like. Can be selected as appropriate.
[0059]
For example, as shown in FIG. 7, a left area 102, a center area 104, and a right area 106 are divided into three parts, although not shown, an upper area, a central area, and a lower area are divided into three parts, as shown in FIG. In FIG. 9, the main subject extracting means extracts only the main subject 120 from the image data and divides it into the required subject 120 and the other region 108, as shown in FIG. Further, as shown in FIG. 10, one frame of image data is divided into, for example, 9 × 5, and six areas (vertical number-horizontal number; 4-7, 4-8) in which the main subject is reflected , 5-7, 5-8, 6-7, 6-8) and other areas. Of course, in the case where there are a plurality of main subjects in different areas, a method of dividing each of the previously divided unit areas or each of the extracted areas can be adopted as described above.
[0060]
In this embodiment, one frame of image data is divided into 9 × 5 unit areas 100 irrespective of the position of the main subject 120, and an appropriate correction amount is calculated for each unit area 100. In this configuration, the granularity of the entire frame of image data is corrected. However, the granularity of the area where the main subject 120 is reflected is accurately corrected, and the granularity of the other areas is roughly corrected. For example, when the correction of the granularity is performed only in the area where the main subject 120 is reflected, the area to be subjected to the correction processing can be limited to selectively correct the granularity. Of course, the entire image data for one frame may be corrected in accordance with the granularity correction value of the area where the main subject 120 is reflected.
[0061]
Further, since the correction amount of the granularity depends on the density of the subject, a density cumulative histogram in which the vertical axis is the number of pixels and the horizontal axis is the density value as shown in FIG. A pixel or area in a preset density range is selected from the density cumulative histogram to perform the granularity correction, or a correction value corresponding to each pixel or area having the same density is applied to the entire image data for one frame or one pixel. It is also possible to adopt a configuration in which granularity correction is performed on a partial area (an area where the main subject is reflected, an area other than the main subject, an area selected by the user, and the like).
[0062]
The granularity has a trade-off relationship with the sharpness enhancement degree, and the granularity correction / sharpness correction unit 220 performs the correction of the granularity together with the sharpness enhancement processing described below based on the correction amount obtained by the above-described method. Do.
[0063]
First, as shown in FIG. 12, subjected to a filtering process by fine scanning data S _F 9 × a low-pass filter of 5 × 5 shown below for _(RGB) and two-stage cascaded 9 low-pass filter 21, the fine scanned data Of the low frequency components R _L , G _L , and B _L.
[0064]
(Equation 1)

Then, it extracts the low frequency components _R L from fine scanning data _{S F,} G L, intermediate and high frequency components _R MH subtracts the _{B L,} G _MH, and _{B MH.} The low frequency components R _L , G _L , and B _L after the extraction do not include roughness due to edges in the color image, fine textures, or film grain. On the other hand, the intermediate frequency components R _M , G _M , and B _M include roughness due to film grain, and the high frequency components R _H , G _H , and B _H include edges and fine textures in a color image.
[0065]
Here, the low frequency components _R L of the fine scanning _data, G L, _{B L,} middle frequency components _{R M,} G _{M, B} M and high frequency components _{R H,} G H, and _{B H} as shown in FIG. 13 The frequency components when the gains M and H by which the distributed middle / high frequency components are multiplied are set to 1.0. The intermediate frequency components R _M , G _M , and B _M have a distribution H _M with a peak near 付 近 of the Nyquist frequency fs / 2 of the output when the processed data is reproduced as a visible image. Refers to frequency components. Further, the low frequency components R _L , G _L , and B _L are components having a peak at 0 frequency and having a distribution H _L, and the high frequency components R _H , G _H , and B _H are the Nyquist frequency fs of the output. / 2 with a peak refers to a component as a distribution H _H.
[0066]
In the present embodiment, the Nyquist frequency refers to the Nyquist frequency when recording on a photosensitive material is performed at 300 dpi. Here, in FIG. 6, the sum of the frequency components is 1 at each frequency.
[0067]
Next, a luminance component is extracted from the decomposed intermediate / high frequency components R _MH , G _MH , and B _MH . In the extraction of the luminance component, the component Y _MH when the intermediate / high frequency components R _MH , G _MH , and B _MH of the fine scan data are converted into the YIQ base represents the luminance component of the data. Here, conversion to the YIQ basis is performed by the following equation.
[0068]
(Equation 2)

Since the component I _MH and the component Q _MH, which are the color components converted into the YIQ basis, include the roughness of the color caused by the film grain, the component I _MH and the component Q _MH are set to 0 here, and the color caused by the film grain is set to 0. Suppresses roughness.
[0069]
Here, it is empirically known that the component I _MH and the component Q _MH, which are color components, have almost no components in the case of an image of a general subject. Therefore, by setting the component I _MH and the component Q _MH to 0, assuming that the color is rough due to the granularity of the film, a good reproduced image in which the roughness is suppressed can be obtained.
[0070]
Then, the component Y _MH is subjected to filtering processing in the gain processing unit using the above-described 5 × 5 low-pass filter, thereby obtaining an intermediate frequency component Y _M of the component Y _MH . Moreover, obtaining a Koma frequency components _{Y H} of the components _{Y MH} by subtracting the intermediate frequency components _{Y M} of component _{Y MH.}
[0071]
Next, the gains M and H obtained by the above-described granularity correction / sharpness correction unit 220 are multiplied by the components Y _M and Y _H , respectively, as shown in the following equation, and the processed components Y _M ′ and Y _H 'is obtained, processed components _{Y M', Y H} 'are combined components _{Y MH'} are obtained.
[0072]
Y _MH ′ = gain M × Y _M + gain H × Y _H (3)
(Y _M ′ = gain M × Y _M , Y _H ′ = gain H × Y _H )
Here, the gain M and the gain H are set in the granularity correction / sharpness correction unit 220 so that the gain M <the gain H. That is, roughness of the luminance component based on the film graininess, because it contains a relatively large amount to an intermediate frequency component, from the setting the gain M of the components Y _M relatively low, it is possible to suppress the graininess. Further, sharpness degree of an image is dependent on the high-frequency component of the luminance component, by relatively increasing the gain H of the high frequency components Y _H of the luminance component, it is possible to emphasize the sharpness of the processed image.
[0073]
For example, when the color image is under negative, the roughness caused by the film graininess is conspicuous, and if the tone is raised to improve the tone characteristics, the image becomes considerably poor in graininess. By setting the gain M to be very low, the granularity can be strongly suppressed.
[0074]
That is, the granularity correction / sharpness correction unit 220 calculates the most appropriate gain M as a correction amount for each of the divided regions by the above-described method, and suppresses the granularity based on the gain M. The gain M is set according to the area of the divided image data, or the gain G and the gain H according to the user's preference are stored as a table, and the gain G and the gain H according to the user's selection are stored in a unit. It is also possible to adopt a configuration in which selection is appropriately made for each region 100.
[0075]
Then, thus component obtained by Y _MH 'low frequency components R _L of the fine scanning data S _F described _above, G _L, B _L and synthesizing the processed signals R', obtain G ', B' . At this time, if the above-described component I _MH ′ is inversely transformed to correspond to RGB data, all three RGB data have the same value as the component Y _MH ′, so that the processed luminance component _MH ′ is not inversely transformed. The processing can be simplified by synthesizing with.
[0076]
After that, the above processing is performed for each unit area 100, and a plurality of processed signals R ′, G ′, and B ′ obtained for each unit area 100 are output to the image data conversion unit 210.
[0077]
【The invention's effect】
As described above, according to the present invention, since the granularity correction of one frame of image data is performed based on the partial image data, the granularity correction is performed according to the difference in granularity in the image imprinted in one frame. This achieves an effect that an image processing apparatus capable of performing fine correction can be obtained.
[Brief description of the drawings]
FIG. 1 is a schematic configuration diagram of a digital laboratory system according to an embodiment of the present invention.
FIG. 2 is a schematic view of a digital laboratory system.
FIG. 3 is a control block diagram of an image processing unit.
FIG. 4 is an explanatory diagram showing a state in which image data for one frame is divided into 9 × 5 unit areas 100;
FIG. 5 is a diagram showing a correlation between density and color (luminance).
FIG. 6 is a diagram showing a correlation between a color (luminance) and a granularity correction amount.
FIG. 7 is an explanatory diagram showing a state in which image data for one frame is divided into a left area 102, a central area 104, and a right area 106;
FIG. 8 is an explanatory diagram showing a state in which image data for one frame is divided into a central area 110 and another area 108.
9 is an explanatory diagram showing a state in which only main subject 120 is extracted from image data of one frame from image data by main subject extracting means and divided into required subject 120 and other area 108. FIG.
FIG. 10 is an explanatory diagram showing a state in which image data for one frame is divided into 9 × 5, and divided into six regions in which a main subject is reflected and other regions.
FIG. 11 is a diagram illustrating an example of a density cumulative histogram calculated from image data of one frame.
FIG. 12 is a block diagram illustrating an example of graininess suppression and sharpness enhancement processing according to the embodiment.
FIG. 13 is a characteristic diagram showing distributions of a low frequency component, an intermediate frequency component, and a high frequency component.
[Explanation of symbols]
Reference Signs List 10 digital laboratory system 14 line CCD scanner 16 image processing unit 66 light source unit 68 photographic film 200 data processing unit 202 log converter 204 prescan memory 206 main scan memory 208 image data processing unit 212 prescan processing unit 214 image data processing unit 218 Main scan processing unit 220 Granularity correction / sharpness correction unit 224 Condition setting unit 234 Lens characteristic data supply unit

Claims (9)

An image processing apparatus that performs predetermined image processing on image data obtained by photoelectrically reading an image recorded on a film and obtains image data for output,
A granularity correction amount calculating unit configured to calculate a correction amount of granularity for each of the predetermined regions based on each density of a plurality of predetermined regions formed by dividing the image data;
A granularity correction for correcting the granularity of the image data based on the correction amount for each predetermined area calculated by the granularity correction amount calculating means, and reflecting the correction amount in a sharpness enhancement process for the image data. Means,
An image processing apparatus having: The image processing apparatus according to claim 1, wherein the granularity correction unit corrects the image data for each predetermined area based on a correction amount corresponding to each predetermined area . The image processing apparatus according to claim 1, wherein the granularity correction unit corrects only image data of the predetermined area at the predetermined position based on a correction amount calculated from the predetermined area at the predetermined position . The image processing apparatus according to claim 1, wherein the predetermined area is an area configured by one pixel . Main subject extracting means for extracting an occupied area of the main subject from the image data,
2. The image processing apparatus according to claim 1, wherein the occupied area extracted by the main subject extracting unit or an area other than the occupied area is selected as the predetermined area . 2. The image processing apparatus according to claim 1, wherein the predetermined area is a set of pixels having a specific density obtained from a density cumulative histogram of the image data . The image processing apparatus according to any one of claims 1 to 6, wherein the density is a relative density difference from an applied film base density . Further provided is a film type determining means for determining a film type,
8. The apparatus according to claim 1, wherein the granularity correction amount calculation unit adjusts a reference value for calculating the correction amount according to a film type from the film type determination unit. 9. Image processing device.   An image processing method of performing predetermined image processing on image data obtained by photoelectrically reading an image recorded on a film to obtain image data for output,
  Based on the respective densities of a plurality of predetermined regions formed by dividing the image data, a correction amount of granularity for each predetermined region is calculated,
  Based on the calculated correction amount for each predetermined area, the granularity of the image data is corrected, and the correction amount is reflected in sharpness enhancement processing on the image data.
  Image processing method.

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