我正在开发一个应用程序，它实时进行图像处理，以获得每帧之间的y和和时间。它们存储在2个双数组中，为了进一步实现，我需要对这些值运行快速傅里叶变换。
我在其他问题中看到了几种fft算法，例如
我还阅读了他们建议使用JTransform library
的主题然而，由于我对FFT的知识非常有限，我不知道如何将它实现到我的代码中。
我的 MainActivity 就是这个
public class MainActivity extends AppCompatActivity implements CameraView.PreviewReadyCallback {
private static Camera camera = null;
private CameraView image = null;
Button fftButton;
private LineChart bp_graph;
private int img_Y_Avg, img_U_Avg, img_V_Avg;
private long end = 0, begin = 0;
Handler handler;
private int readingRemaining = 1200;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON);
bp_graph = (LineChart)findViewById(R.id.graph);
fftButton = (Button)findViewById(R.id.runFFT);
graph_features();
//open camera
try {
camera = Camera.open();
handler = new Handler();
final Runnable runnable = new Runnable() {
@Override
public void run() {
camera.stopPreview();
camera.release();
fftButton.setVisibility(View.VISIBLE);
}
};
handler.postDelayed(runnable, 30000);
} catch (Exception e) {
Log.d("ERROR", "Failed to get camera: " + e.getMessage());
}
if (camera != null) {
image = new CameraView(this, camera);
FrameLayout camera_view = (FrameLayout) findViewById(R.id.camera_view);
camera_view.addView(image);
image.setOnPreviewReady(this);
}
}
@Override
protected void onResume(){
super.onResume();
}
@Override
protected void onPause() {
super.onPause();
}
@Override
public void onPreviewFrame(long startTime, int ySum, int uSum, int vSum, long endTime) {
begin = startTime;
img_Y_Avg = ySum;
img_U_Avg = uSum;
img_V_Avg = vSum;
end = endTime;
showResults(begin, img_Y_Avg, img_U_Avg, img_V_Avg, end);
}
private void showResults(long startTime, int ySum, int uSum, int vSum, long endTime){
//set value of Y on the text view
TextView valueOfY = (TextView)findViewById(R.id.valueY);
//valueY = img_Y_Avg;
valueOfY.setText(String.valueOf(img_Y_Avg));
//start time in milliseconds
long StartDurationInMs = TimeUnit.MILLISECONDS.convert(begin, TimeUnit.MILLISECONDS);
ArrayList<Long> startOfTime = new ArrayList<>();
startOfTime.add(StartDurationInMs);
//store value to array list
ArrayList<Integer> yAverage = new ArrayList<>();
yAverage.add(img_Y_Avg);
ArrayList<Long> getValues = new ArrayList<>();
for(int i = 0; i < yAverage.size(); i++) {
getValues.add(startOfTime.get(i));
getValues.add((long)(yAverage.get(i)));
}
storeCsv(yAverage, getValues);
Log.d("MyEntryData", String.valueOf(getValues));
}
/**
* method to store raw time and y-sum data into CSV file**/
public void storeCsv(ArrayList<Integer>yAverage, ArrayList<Long>getValues){
String filename = "temporary.csv";
//File directoryDownload = Environment.getExternalStoragePublicDirectory(Environment.DIRECTORY_DOWNLOADS);
String path = Environment.getExternalStorageDirectory().getAbsolutePath() + "/bpReader";
//File logDir = new File (directoryDownload, "bpReader"); //Creates a new folder in DOWNLOAD directory
File logDir = new File(path);
logDir.mkdirs();
File file = new File(logDir, filename);
FileOutputStream outputStream = null;
try {
file.createNewFile();
outputStream = new FileOutputStream(file, true);
//outputStream = openFileOutput(filename, Context.MODE_PRIVATE);
for (int i = 0; i < yAverage.size(); i += 2) {
outputStream.write((getValues.get(i) + ",").getBytes());
outputStream.write((getValues.get(i + 1) + "\n").getBytes());
//outputStream.write((getValues.get(i + 2) + ",").getBytes());
//outputStream.write((getValues.get(i + 3) + "\n").getBytes());
}
outputStream.flush();
outputStream.close();
} catch (Exception e) {
e.printStackTrace();
}
}
//Method for button which appears after the reading is done and the data is saved into csv file
public void readFile(View view){
readCsv();
}
//Method to read the data from the csv and get the time and y-sum value
public void readCsv(){
String getPath = Environment.getExternalStorageDirectory() + "/bpReader";
String csvFile = "temporary.csv";
String path = getPath+ "/" + csvFile;
int length = 500;
double[] xCoords = new double[length];
double[] yCoords = new double[length];
double[] newXcord = new double[length];
CSVReader reader;
try {
File myFile = new File (path);
reader = new CSVReader(new FileReader(myFile));
String[] line;
int i;
for (i = 0; i < xCoords.length; i ++){
if ((line = reader.readNext()) != null){
xCoords[i] = Double.parseDouble(line[0]);
yCoords[i] = Double.parseDouble(line[1]);
}
}
for (i = 0; i < xCoords.length ; i++){
if (xCoords[i]!=0) {
newXcord[i] = xCoords[i] - xCoords[0];
Log.d("read:: ", "Time: " + String.valueOf(newXcord[i]) + " Y-Sum " + String.valueOf(yCoords[i]));
}
}
myFile.delete();
} catch (IOException e) {
e.printStackTrace();
}
}
}
}
在我用readCsv()方法读取CSV文件后，我得到这样的数据
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 0.0 Y-Sum 570194.0
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 50.0 Y-Sum 405504.0
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 118.0 Y-Sum 405504.0
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 168.0 Y-Sum 405504.0
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 234.0 Y-Sum 429242.0
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 301.0 Y-Sum 1217635.0
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 368.0 Y-Sum 1516666.0
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 418.0 Y-Sum 1495037.0
10-15 16:37:50.127 16912-16912/redlight55.com.bpreader D/read::: Time: 486.0 Y-Sum 1514453.0
10-15 16:37:50.128 16912-16912/redlight55.com.bpreader D/read::: Time: 553.0 Y-Sum 1507075.0
10-15 16:37:50.128 16912-16912/redlight55.com.bpreader D/read::: Time: 625.0 Y-Sum 1511241.0
10-15 16:37:50.128 16912-16912/redlight55.com.bpreader D/read::: Time: 678.0 Y-Sum 1476090.0
10-15 16:37:50.128 16912-16912/redlight55.com.bpreader D/read::: Time: 749.0 Y-Sum 1476961.0
10-15 16:37:50.128 16912-16912/redlight55.com.bpreader D/read::: Time: 815.0 Y-Sum 1470232.0
我的 FFT类是我从其他堆栈溢出问题中的一些建议中得到的。
public class FFT {
/**
* The Fast Fourier Transform (generic version, with NO optimizations).
*
* @param inputReal
* an array of length n, the real part
* @param inputImag
* an array of length n, the imaginary part
* @param DIRECT
* TRUE = direct transform, FALSE = inverse transform
* @return a new array of length 2n
*/
public static double[] fft(final double[] inputReal, double[] inputImag,
boolean DIRECT) {
// - n is the dimension of the problem
// - nu is its logarithm in base e
int n = inputReal.length;
// If n is a power of 2, then ld is an integer (_without_ decimals)
double ld = Math.log(n) / Math.log(2.0);
// Here I check if n is a power of 2. If exist decimals in ld, I quit
// from the function returning null.
if (((int) ld) - ld != 0) {
System.out.println("The number of elements is not a power of 2.");
return null;
}
// Declaration and initialization of the variables
// ld should be an integer, actually, so I don't lose any information in
// the cast
int nu = (int) ld;
int n2 = n / 2;
int nu1 = nu - 1;
double[] xReal = new double[n];
double[] xImag = new double[n];
double tReal, tImag, p, arg, c, s;
// Here I check if I'm going to do the direct transform or the inverse
// transform.
double constant;
if (DIRECT)
constant = -2 * Math.PI;
else
constant = 2 * Math.PI;
// I don't want to overwrite the input arrays, so here I copy them. This
// choice adds \Theta(2n) to the complexity.
for (int i = 0; i < n; i++) {
xReal[i] = inputReal[i];
xImag[i] = inputImag[i];
}
// First phase - calculation
int k = 0;
for (int l = 1; l <= nu; l++) {
while (k < n) {
for (int i = 1; i <= n2; i++) {
p = bitReverseReference(k >> nu1, nu);
// direct FFT or inverse FFT
arg = constant * p / n;
c = Math.cos(arg);
s = Math.sin(arg);
tReal = xReal[k + n2] * c + xImag[k + n2] * s;
tImag = xImag[k + n2] * c - xReal[k + n2] * s;
xReal[k + n2] = xReal[k] - tReal;
xImag[k + n2] = xImag[k] - tImag;
xReal[k] += tReal;
xImag[k] += tImag;
k++;
}
k += n2;
}
k = 0;
nu1--;
n2 /= 2;
}
// Second phase - recombination
k = 0;
int r;
while (k < n) {
r = bitReverseReference(k, nu);
if (r > k) {
tReal = xReal[k];
tImag = xImag[k];
xReal[k] = xReal[r];
xImag[k] = xImag[r];
xReal[r] = tReal;
xImag[r] = tImag;
}
k++;
}
// Here I have to mix xReal and xImag to have an array (yes, it should
// be possible to do this stuff in the earlier parts of the code, but
// it's here to readibility).
double[] newArray = new double[xReal.length * 2];
double radice = 1 / Math.sqrt(n);
for (int i = 0; i < newArray.length; i += 2) {
int i2 = i / 2;
// I used Stephen Wolfram's Mathematica as a reference so I'm going
// to normalize the output while I'm copying the elements.
newArray[i] = xReal[i2] * radice;
newArray[i + 1] = xImag[i2] * radice;
}
return newArray;
}
/**
* The reference bitreverse function.
*/
private static int bitReverseReference(int j, int nu) {
int j2;
int j1 = j;
int k = 0;
for (int i = 1; i <= nu; i++) {
j2 = j1 / 2;
k = 2 * k + j1 - 2 * j2;
j1 = j2;
}
return k;
}
}
我的问题是
readCsv方法中执行fft并在读取所有值后使用值作为输入。