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The revision history describes the changes that were implemented in the document. The changes are
listed by revision, starting with the most current publication.
1.1Revision 4.0
Steps to simulate the core using test bench were added. For more information, see Testbench, page 7.
1.2Revision 3.0
The following is a summary of the changes in revision 3.0 of this document.
•Configuration parameters were updated. For more information, see Table 2, page 5.
•Timing diagram was updated. For more information, see Figure 4, page 7.
•Information about image buffer 0 and image buffer 1 was added. For more information, see
Hardware Implementation, page 3.
•Information about FSM states was updated. For more information, see FSM Implementation,
page 6.
1.3Revision 2.0
The following is a summary of the changes in revision 2.0 of this document.
•Table 3, page 7 was added.
•Table 1, page 4 and Ta bl e 4 , page 12 were updated.
•Figure 2, page 4 and Figure 4, page 7 were updated.
1.4Revision 1.0
Revision 1.0 was the first publication of this document.
UG0651 User Guide Revision 4.0vi
Page 7
Introduction
2Introduction
Image scaling is a process of constructing a resized image from a given input image. The constructed
image can be smaller, larger, or equal in size, depending on the scaling ratio. While scaling up an image,
empty spaces are introduced in the base image. The following figure shows an image at its original
dimensions (2x2) and at scaled-up dimensions (4x4). The white pixels represent empty spaces where
interpolation is required, and the complete picture is the result of the nearest neighbor interpolation.
Interpolation algorithms attempt to generate continuous data from a set of discrete data samples through
an interpolation function. The interpolation algorithms minimize the visual defects arising from the
inevitable resampling error and improve the quality of the resampled images. The interpolation function is
performed by the convolution operation that involves a large number of additions and multiplications.
However, a trade-off is required between the computation complexity and quality of the scaled image.
Based on the content awareness of the algorithm, the image scaling algorithms are classified as adaptive
image scaling and non-adaptive image scaling.
Adaptive image scaling algorithms modify their interpolation technique based on whether the image has
a smooth texture or a sharp edge. The interpolation method changes in real-time, therefore these
algorithms are complex and computationally intensive. They find widespread use in image editing
software, as they ensure a high quality scaled image.
Non-adaptive image scaling algorithms such as nearest neighbor, bilinear, bicubic, and Lanczos
algorithms have a fixed interpolation method irrespective of the image content.
Using the nearest neighbor algorithm, image scaling is performed by interpolating a pixel's color and
intensity values (horizontally and vertically) based on the values of neighboring pixels. The nearest
neighbor algorithm is used to find the empty spaces in the original image, and to replace them with the
nearest neighboring pixel.
UG0651 User Guide Revision 4.01
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Introduction
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UG0651 User Guide Revision 4.02
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Hardware Implementation
X
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3Hardware Implementation
The scaler module contains two internal buffers that can store one line of the image for processing—
Image_Buffer0_i and Image_Buffer1_i. Each line of input data is written to Image_Buffer0_i and
Image_Buffer1_i, alternately. The line_ready signal indicates that the scaler can start processing the next
line. It must be set to high after the input line write to the buffer is completed.
With the exception of the first line, after one line of data is input to the scaler, the next line must be input
only after the Line_Done_o signal goes high. For a new frame, the first two lines of the frame need to be
input before the scaler starts processing the data.
The data stored in the image buffer is scaled to calculate the output data based on the nearest neighbor
algorithm.
When downscaling the height of the image, the next input line to the scaler must begin with the pixel
number mentioned in NxtLine_PixelNum_Offset_o. When upscaling, the value of
NxtLine_PixelNum_Offset_o is the first pixel of the next line in sequence.
The following equations are used to calculate scaling factors for horizontal and vertical resolutions:
UG0651 User Guide Revision 4.03
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Hardware Implementation
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The following figure shows the scaler block diagram.
Figure 2 • Scaler Block Diagram
3.1Inputs and Outputs
The following table describes the input and output ports.
Table 1 • Scaler Input and Output Ports
Directio
Signal Name
nWidthDescription
nReset_IInput –Active low asynchronous reset signal to
SYS_CLK_I Input –System clock.
DATA_In_iInput [g_DATA_BITWIDTH * g_CHANNELS - 1 : 0] Input data to scaler.
DATAIn_VLD_iInput –Set when input data is valid.
Start_iInput –Scaler start signal. To be set to high
design.
before loading a new frame.
UG0651 User Guide Revision 4.04
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Hardware Implementation
Table 1 • Scaler Input and Output Ports (continued)
DATAOut_VLD_o Output –Sets when output data is a valid register
line_readyInput–Set when writing the current line to the
Output[(g_INPUT_Y_RES_BITWIDTH+g_INPUT_
X_RES_BITWIDTH - 1): 0]
Indicates the pixel number of the source
image from which the next line is to be
dumped into the scaler image buffer.
When downscaling height wise, this signal
indicates the next line in sequence.
and describes the output of the scaler.
image buffer is complete, indicating that
buffer data is ready for processing.
3.2Configuration Parameters
The following table describes the configuration parameters used in the hardware implementation of the
scaler. These are generic parameters and can vary based on the application requirements.
Table 2 • Configuration Parameters
NameDescription
g_DATA_BITWIDTHWidth of the data input or output
g_CHANNELSNumber of data channels
g_INPUT_X_RES_BITWIDTHInput resolution X bit width
g_INPUT_Y_RES_BITWIDTHInput resolution Y bit width
g_OUTPUT_X_RES_BITWIDTHOutput resolution X bit width
g_OUTPUT_Y_RES_BITWIDTHOutput resolution Y bit width
g_SCALE_FACTOR_BITWIDTHScaling factor bit width
g_SF_ROUNDING_PRECISIONScaling factor's rounding precision bit width. Default value
is configured to 256 (2
g_BUFF_DEPTHLine buffer depth
8
).
UG0651 User Guide Revision 4.05
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Hardware Implementation
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3.3FSM Implementation
The scaler finite state machine (FSM) goes through the following states during implementation:
•IDLE: After the module is reset or frame processing is complete, the FSM goes to IDLE state and
waits for the start signal to move to the RAM_FULL_CHECK state.
•RAM_FULL_CHECK: The FSM remains in this state until the write to the image buffer is completed
and line_ready signal is received. Then, it moves to the INP_PIXEL_INC state.
•INP_PIXEL_INC: The FSM moves to the NXT_PIXEL state in the next cycle.
•NXT_PIXEL: The FSM moves to WAIT_STATE in the next cycle.
•WAIT_STATE: The FSM moves to DATAOUT state in the next cycle.
•DATAOUT: The output pixel is calculated based on the horizontal counter, vertical counter, and
scaling factors. The horizontal and vertical counters are updated and the read address and read
enable signal (for reading from one of the two image buffers) is generated. On completion of
processing of one input line, the FSM moves to RAM_FULL_CHECK state. After the total frame data
is output, the FSM moves to IDLE state.
The following figure shows the scaler FSM implementation.
Figure 3 • Scaler FSM States
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UG0651 User Guide Revision 4.06
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Hardware Implementation
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3.4Timing Diagram
The following figure shows the timing diagram of the scaler.
Figure 4 • Timing Diagram
3.5Testbench
A testbench is provided to check the functionality of the scaler core. The following table lists the
parameters that can be configured according to the application.
Table 3 • Testbench Configuration Parameters
NameDescription
CLKPERIODClock period
IN_HEIGHTHeight of the input image
IN_WIDTHWidth of the input image
OUT_HEIGHTHeight of the output frame
OUT_WIDTHWidth of the output frame
IMAGE_FILE_NAMEInput file name
UG0651 User Guide Revision 4.07
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Hardware Implementation
The following steps describe how to simulate the core using the testbench.
1.In the Design Flow window, expand Create Design. Right-click Create SmartDesignTestbench
and click Run, as shown in the following figure.
Figure 5 • Create SmartDesign Testbench
2.Enter a name for the SmartDesign testbench in the dialog box, and click OK.
Figure 6 • Create New SmartDesign Testbench Dialog Box
A SmartDesign testbench is created, and a canvas appears to the right of the Design Flow pane.
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Hardware Implementation
3.In the Catalog window, expand Solutions-Video, and drag the Scaler core onto the SmartDesign
testbench canvas.
Figure 7 • Scaler
The core appears on the canvas, as shown in the following figure.
Figure 8 • Scaler Core on SmartDesign Testbench Canvas
4.Select all the ports of the core, right-click, and then click Promote to Top Level, as shown in the
following figure.
Figure 9 • Promote to Top Level Option
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Hardware Implementation
The ports are promoted to the top-level, as shown in the following figure.
Figure 10 • Scaler Ports Promoted to Top Level
5.From the SmartDesign toolbar, click the Generate Component highlighted in the following figure.
Figure 11 • Generate Component
6.In the Files window, right-click the simulation directory, and click Import files..., as shown in the
following figure.
Figure 12 • Import Files Option
UG0651 User Guide Revision 4.010
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Hardware Implementation
7.Do one of the following:
•To import the sample testbench input file, browse to sample testbench input file to the stimulus
directory, and click Open, as shown in the following figure.
A sample RGB_in.txt file is provided with the testbench at the following path:
..\Project_name\component\Microsemi\SolutionCore\Scaler\2.0.0\Stimulus
•To import a different file, browse to the folder containing the image file, and click Open.
Figure 13 • Input File Selection
The imported file is listed under simulation as shown in the following figure.
Figure 14 • Input File in Simulation Directory
8.In the Stimulus Hierarchy, expand Work, and right-click Scaler_test (Scaler_tb.v). Select
Simulate Pre-Synth Design, then click Open Interactively.
Figure 15 • Simulating Pre-Synthesis Design
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Hardware Implementation
The ModelSim tool appears with the testbench file loaded on to it, as shown in the following figure.
Figure 16 • ModelSim Tool with Scaler Testbench File
9.If the simulation is interrupted because of the runtime limit in the DO file, use the run -all
command in the transcript window to complete the simulation.
After the simulation is completed, the testbench output image file appears in the simulation folder.
3.6Resource Utilization
The scaler is implemented in the SmartFusion®2 system-on-chip (SoC) FPGA (M2S150T-1FC1152
package). The following table lists the resources used by the FPGA.
Table 4 • Resource Utilization Report
ResourceUsage
DFFs328
4-Input LUTs525
MACC3
RAM1Kx182
RAM64x180
UG0651 User Guide Revision 4.012
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