Image segmentation method and image processing apparatus

An image processing apparatus, comprising:

• a processor;
• and
• a memory storing instructions that when executed by the processor configure the image processing apparatus to:
• obtain an input image and a processing requirement, wherein the processing requirement is used to indicate to perform target processing on a target feature map group obtained by performing image segmentation on the input image;
• and
• perform multi-layer feature extraction on the input image to obtain a plurality of feature maps;
• downsample the plurality of feature maps to obtain a plurality of feature maps with a reference resolution, wherein the reference resolution is less than a resolution of the input image;
• fuse the plurality of feature maps with the reference resolution to obtain at least one feature map group;
• upsample the at least one feature map group by using a transformation matrix W, to obtain the target feature map group, wherein the target feature map group has a same resolution as that of the input image, the transformation matrix W is obtained by modeling training data of an image segmentation task, and one dimension of the transformation matrix W is the same as a quantity of channels of the feature group;
• and
• perform the target processing on the target feature map group based on the processing requirement to obtain a target image.

A non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores a computer program, the computer program comprises a program instruction, and when the program instruction is executed by a processor, the processor is configured to perform steps comprising:

• obtaining an input image and a processing requirement, wherein the processing requirement is used to indicate to perform target processing on a target feature map group obtained by performing image segmentation on the input image;
• performing multi-layer feature extraction on the input image to obtain a plurality of feature maps;
• downsampling the plurality of feature maps to obtain a plurality of feature maps with a reference resolution, wherein the reference resolution is less than a resolution of the input image;
• fusing the plurality of feature maps with the reference resolution to obtain at least one feature map group;
• upsampling the at least one feature map group by using a transformation matrix W, to obtain the target feature map group, wherein the target feature map group has a same resolution as that of the input image, the transformation matrix W is obtained by modeling training data of an image segmentation task, and one dimension of the transformation matrix W is the same as a quantity of channels of the feature group;
• and
• performing the target processing on the target feature map group based on the processing requirement to obtain a target image.