Information processing apparatus using class-classification adaptive processing

An information processing method comprising the steps of:

• classifying an aimed-at data item into one of a plurality of classes specified in advance, according to a plurality of data items disposed around the aimed-at data item;
• selecting conversion information corresponding to the class into which the aimed-at data item has been classified;
• and
• converting the aimed-at data item to a data item having a higher quality, according to the conversion information,
• wherein the aimed-at data item is classified into a different class according to a missing condition of the aimed-at data item and/or or more data items disposed around the aimed-at data item, in the step of classifying the aimed-at data item.

A recording medium storing a computer-readable program, the program comprising the steps of:

• classifying an aimed-at data item into one of a plurality of classes specified in advance, according to a plurality of data items disposed around the aimed-at data item;
• selecting conversion information corresponding to the class into which the aimed-at data item has been classified;
• and
• converting the aimed-at data item to a data item having a higher quality, according to the conversion information,
• wherein the aimed-at data item is classified into a different class according to at least one of a missing condition of the aimed-at data item and one or more data items disposed around the aimed-at data item, in the step of classifying the aimed-at data item.

A learning apparatus comprising:

• a class classifier for classifying an aimed-at data item into one of a plurality of classes specified in advance, according to a plurality of data items disposed around the aimed-at data item;
• and
• a conversion-information generator for generating conversion information used for converting the aimed-at data item to a data item having a higher quality, for the class,
• wherein the class classifier classifies the aimed-at data item into a different class according to a missing condition of the aimed-at data item and one or more data items disposed around the aimed-at data item.

A learning method comprising the steps of:

• classifying an aimed-at data item into one of a plurality of classes specified in advance, according to a plurality of data items disposed around the aimed-at data item;
• and
• generating conversion information used for converting the aimed-at data item to a data item having a higher quality, for the class,
• wherein the aimed-at data item is classified into a different class in the step of classifying the aimed-at data item, according to a missing condition of the aimed-at data item and/or one or more data items disposed around the aimed-at data item.